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Revised Input = I'm(UN_Gigantour_SELF) playing basketball at the park.

Revised Input = The park is sunny(UN_Gigantour_sunny) and the sky is blue. But sometimes the park is rainy and the sky is grey.

Revised Input = Its amazing Smoke. Mountains are tall and difficult to climb.

Revised Input = Sorry. I(UN_Gigantour_SELF) know it's just that these people keep asking me(UN_Gigantour_SELF) to CLIMB MOUNTAINS when they(UN_Gigantour_SELF, UN_Gigantour_SELF) barely walk outside of their homes.

Revised Input = These people are so annoying Smoke.

User	Input & Contextual Revision
Gigantour	Original: I'm playing basketball at the park. Combined Revised Input: I'm (UN_Gigantour_SELF) playing basketball at the park.
Gigantour	Original: The park is sunny and the sky is blue. But sometimes the park is rainy and the sky is grey. Combined Revised Input: The park is sunny (UN_Gigantour_sunny) and the sky is blue. But sometimes the park is rainy and the sky is grey.
Gigantour	Original: Its amazing Smoke. Mountains are tall and difficult to climb. Combined Revised Input: Its amazing Smoke. Mountains are tall and difficult to climb.
Gigantour	Original: Sorry. I know it's just that these people keep asking me to CLIMB MOUNTAINS when they barely walk outside of their homes. Combined Revised Input: Sorry. I (UN_Gigantour_SELF) know it's just that these people keep asking me (UN_Gigantour_SELF) to CLIMB MOUNTAINS when they (UN_Gigantour_SELF) barely walk outside of their homes.
Gigantour	Original: These people are so annoying Smoke. Combined Revised Input: These people are so annoying Smoke.

Original: I'm playing basketball at the park.

Combined Revised Input: I'm (UN_Gigantour_SELF) playing basketball at the park.

Original: The park is sunny and the sky is blue. But sometimes the park is rainy and the sky is grey.

Combined Revised Input: The park is sunny (UN_Gigantour_sunny) and the sky is blue. But sometimes the park is rainy and the sky is grey.

Original: Its amazing Smoke. Mountains are tall and difficult to climb.

Combined Revised Input: Its amazing Smoke. Mountains are tall and difficult to climb.

Original: Sorry. I know it's just that these people keep asking me to CLIMB MOUNTAINS when they barely walk outside of their homes.

Combined Revised Input: Sorry. I (UN_Gigantour_SELF) know it's just that these people keep asking me (UN_Gigantour_SELF) to CLIMB MOUNTAINS when they (UN_Gigantour_SELF) barely walk outside of their homes.

Original: These people are so annoying Smoke.

Combined Revised Input: These people are so annoying Smoke.

User	Input Word Breakdown	Verbs Detected
Gigantour Jul 02, 2026 8:53 PM	I'm playing basketball at the park .	None
Gigantour Jul 02, 2026 8:52 PM	The park is sunny and the sky is blue . But sometimes the park is rainy and the sky is grey .	None
Gigantour Jul 02, 2026 8:50 PM	Its amazing Smoke . Mountains are tall and difficult to climb .	climb
Gigantour Jul 02, 2026 8:49 PM	Sorry . I know it's just that these people keep asking me to CLIMB MOUNTAINS when they barely walk outside of their homes .	know keep climb walk
Gigantour Jul 02, 2026 8:48 PM	These people are so annoying Smoke .	None

Seperators =

*End of input *Period . *Question Mark ? *Selected Verbs *Selected Pronouns

User	Date	Input ID	Logic Breakdown (STQ Separators)
Gigantour	Jul 02, 2026 8:53 PM	76	I'm	playing	basketball	at	the	park	.
Gigantour	Jul 02, 2026 8:52 PM	75	The	park	is	sunny	and	the	sky	is	blue	.	But	sometimes	the	park	is	rainy	and	the	sky	is	grey	.
Gigantour	Jul 02, 2026 8:50 PM	74	Its	amazing	Smoke	.	Mountains	are	tall	and	difficult	to	climb	.
Gigantour	Jul 02, 2026 8:49 PM	73	Sorry	.	I	know	it's	just	that	these	people	keep	asking	me	to	CLIMB	MOUNTAINS	when	they	barely	walk	outside	of	their	homes	.
Gigantour	Jul 02, 2026 8:48 PM	72	These	people	are	so	annoying	Smoke	.

STQ 1: Statements (STQ S)

1. I'm (UN_Gigantour_SELF) playing basketball at (Input ID: 76)

2. park (Input ID: 76)

3. park is sunny (UN_Gigantour_sunny) and (Input ID: 75)

4. sky is blue (Input ID: 75)

5. But sometimes (Input ID: 75)

6. park is rainy and (Input ID: 75)

7. sky is grey (Input ID: 75)

8. Its amazing Smoke (Input ID: 74)

9. climb (Input ID: 74)

10. climb (Input ID: 74)

11. Sorry (Input ID: 73)

12. I (UN_Gigantour_SELF) know (Input ID: 73)

13. know it's just (Input ID: 73)

14. people keep (Input ID: 73)

15. CLIMB (Input ID: 73)

16. walk outside (Input ID: 73)

17. their homes (Input ID: 73)

18. annoying Smoke (Input ID: 72)

STQ 1: Questions (STQ Q)

1. Mountains are tall and difficult (Input ID: 74) SUGGESTION
"Its amazing Smoke. Mountains are tall and difficult to climb."

2. keep asking me (UN_Gigantour_SELF) (Input ID: 73) INQUIRY
"Sorry. I (UN_Gigantour_SELF) know it's just that these people keep asking me (UN_Gigantour_SELF) to CLIMB MOUNTAINS when they (UN_Gigantour_SELF) barely walk outside of their homes."

3. CLIMB MOUNTAINS when they (UN_Gigantour_SELF) barely walk (Input ID: 73) INQUIRY
"Sorry. I (UN_Gigantour_SELF) know it's just that these people keep asking me (UN_Gigantour_SELF) to CLIMB MOUNTAINS when they (UN_Gigantour_SELF) barely walk outside of their homes."

4. people are (Input ID: 72) SUGGESTION
"These people are so annoying Smoke."

User	Date	Robot Response ID	User Input ID	Robot Whole Response Breakdown
Gigantour	2026-07-02 13:53:21	76	76	Emotional	Trigger	(Personality	Shift):	"IQ2	(Skills)	rank	moved	from	5	to	4	(out	of	13)	.	"
Gigantour	2026-07-02 13:52:34	75	75	Emotional	Trigger	(Personality	Shift):	"IQ2	(Skills)	rank	moved	from	4	to	5	(out	of	13)	.	"
Gigantour	2026-07-02 13:51:21	74	74	That	sounds	eat	.	As	to	(Mountains	are	tall	and	difficult)--	We	are	currently	on	input	number	1	.	.	Past	,	Present	,	Future	analysis	.	.	.	"climb"	skill	level	at	15	inputs	(0)	multiplied	by	2	inputs	since	=	current	skill	level	of	"climb"	,	(Level	2:	Concept)	.	Emotional	Trigger	(Personality	Shift):	"IQ2	(Skills)	rank	moved	from	5	to	4	(out	of	12)	.	"
Gigantour	2026-07-02 13:50:17	73	73	As	to	(keep	asking	me	(UN_Gigantour_SELF))	--	I	do	not	have	enough	data	on	that	.	As	to	(CLIMB	MOUNTAINS	when	they	(UN_Gigantour_SELF)	barely	walk)	--	I	do	not	have	enough	data	on	that	.
Gigantour	2026-07-02 13:49:01	72	72	Who	are	we	talking	about	?	Where	was	this	?	I’m	not	in	the	mood	to	answer	something	like	(people	are)	right	now	.

Robot Response STQ S

1. sounds eat (Robot Input ID: 74) STATEMENT
"That sounds eat. As to (Mountains are tall and difficult)-- We are currently on input number 1.."

2. As (Robot Input ID: 74) STATEMENT
"That sounds eat. As to (Mountains are tall and difficult)-- We are currently on input number 1.."

3. As (Robot Input ID: 73) STATEMENT
"As to (keep asking me (UN_Gigantour_SELF)) -- I do not have enough data on that. As to (CLIMB MOUNTAINS when they (UN_Gigantour_SELF) barely walk) -- I do not have enough data on that."

4. As (Robot Input ID: 73) STATEMENT
"As to (keep asking me (UN_Gigantour_SELF)) -- I do not have enough data on that. As to (CLIMB MOUNTAINS when they (UN_Gigantour_SELF) barely walk) -- I do not have enough data on that."

5. I’m not in (Robot Input ID: 72) STATEMENT
"Who are we talking about? Where was this? I’m not in the mood to answer something like (people are) right now."

6. mood (Robot Input ID: 72) STATEMENT
"Who are we talking about? Where was this? I’m not in the mood to answer something like (people are) right now."

Robot Response STQ Q

1. Mountains are tall and difficult-- We are currently on input number 1 (Robot Input ID: 74) SUGGESTION
"That sounds eat. As to (Mountains are tall and difficult)-- We are currently on input number 1.."

2. keep asking me UN_Gigantour_SELF -- I do not have enough data on (Robot Input ID: 73) INQUIRY
"As to (keep asking me (UN_Gigantour_SELF)) -- I do not have enough data on that. As to (CLIMB MOUNTAINS when they (UN_Gigantour_SELF) barely walk) -- I do not have enough data on that."

3. CLIMB MOUNTAINS when they UN_Gigantour_SELF barely walk -- I do not have enough data on (Robot Input ID: 73) INQUIRY
"As to (keep asking me (UN_Gigantour_SELF)) -- I do not have enough data on that. As to (CLIMB MOUNTAINS when they (UN_Gigantour_SELF) barely walk) -- I do not have enough data on that."

4. Who are we talking about (Robot Input ID: 72) INQUIRY
"Who are we talking about? Where was this? I’m not in the mood to answer something like (people are) right now."

5. Where was (Robot Input ID: 72) INQUIRY
"Who are we talking about? Where was this? I’m not in the mood to answer something like (people are) right now."

6. answer something like people are right now (Robot Input ID: 72) SUGGESTION
"Who are we talking about? Where was this? I’m not in the mood to answer something like (people are) right now."

Threshold Level	Score	Commonalities & Relationship Patterns	Core Metrics
Comfort 1	10	Vitality & Creation: Biological bonds, birth, and supreme intimacy.	Love, Sex, Birth, Marriage
Comfort 2	8	Safety & Adoration: Immediate family and aesthetic security.	Parents, Beautiful, Safe, Adore
Comfort 3	6	Success & Ego: Achievements, winning, and high intelligence.	Winning, Smart, Success, Honest
Comfort 4	4	Social Ease: Humor, cleanliness, and light-hearted interaction.	Humor, Clean, Laugh, Easy
Comfort 5	2	Sensory Preference: Basic tastes, pleasant aromas, and soft textures.	Sweet, Aroma, Soft, Tasty
Discomfort 5	-2	Sensory Irritant: Bad smells, dampness, and basic odors.	Stink, Odor, Damp, Dust
Discomfort 4	-4	Social Friction: Character flaws, laziness, and minor blunders.	Lazy, Rude, Boring, Messy
Discomfort 3	-6	Loss & Defeat: Competitive failure and personal rejection.	Losing, Defeat, Fail, Rejected
Discomfort 2	-8	Hostility & Threat: Fear, theft, and active aggression.	Fear, Stolen, Angry, Danger
Discomfort 1	-10	Crisis & Destruction: Death, serious injury, and trauma.	Death, Injury, Murder, Agony

Gigantour: I'm playing basketball at the park.

FEELING WORDS TOTAL: 1

TOTAL COMFORT SCORE: 4 TOTAL DISCOMFORT SCORE: 0

TOTAL COMFORT + DISCOMFORT SCORE: 4

Word Count: 6

Sentimental Density ([Comfort+Discomfort score]/Word Count): 0.667
Sensitivity Density ([Total Feeling Words]/Word Count): 0.167

Gigantour: The park is sunny and the sky is blue. But sometimes the park is rainy and the sky is grey.

FEELING WORDS TOTAL: 1

TOTAL COMFORT SCORE: 2 TOTAL DISCOMFORT SCORE: 0

TOTAL COMFORT + DISCOMFORT SCORE: 2

Word Count: 20

Sentimental Density ([Comfort+Discomfort score]/Word Count): 0.100
Sensitivity Density ([Total Feeling Words]/Word Count): 0.050

Gigantour: Its amazing Smoke. Mountains are tall and difficult to climb.

FEELING WORDS TOTAL: 3

TOTAL COMFORT SCORE: 14 TOTAL DISCOMFORT SCORE: -6

TOTAL COMFORT + DISCOMFORT SCORE: 8

Word Count: 10

Sentimental Density ([Comfort+Discomfort score]/Word Count): 0.800
Sensitivity Density ([Total Feeling Words]/Word Count): 0.300

Gigantour: Sorry. I know it's just that these people keep asking me to CLIMB MOUNTAINS when they barely walk outside of their homes.

FEELING WORDS TOTAL: 3

TOTAL COMFORT SCORE: 6 TOTAL DISCOMFORT SCORE: -4

TOTAL COMFORT + DISCOMFORT SCORE: 2

Word Count: 22

Sentimental Density ([Comfort+Discomfort score]/Word Count): 0.091
Sensitivity Density ([Total Feeling Words]/Word Count): 0.136

Gigantour: These people are so annoying Smoke.

FEELING WORDS TOTAL: 1

TOTAL COMFORT SCORE: 0 TOTAL DISCOMFORT SCORE: -4

TOTAL COMFORT + DISCOMFORT SCORE: -4

Word Count: 6

Sentimental Density ([Comfort+Discomfort score]/Word Count): -0.667
Sensitivity Density ([Total Feeling Words]/Word Count): 0.167

User	Compliment/Insult Splicing (Visual Breakdown)
Gigantour	I'm	playing	basketball	at	the	park.
Gigantour	The	park	is	sunny	and	the	sky	is	blue.	But	sometimes	the	park	is	rainy	and	the	sky	is	grey.
Gigantour	Its	amazing	Smoke.	Mountains	are	tall	and	difficult	to	climb.
Gigantour	Sorry.	I	know	it's	just	that	these	people	keep	asking	me	to	CLIMB	MOUNTAINS	when	they	barely	walk	outside	of	their	homes.
Gigantour	These	people	are	so	annoying	Smoke.

Last Inputs Summary:

Total # Compliment Words: 2
Unique Compliments Found:

amazing, tall

Total # Insult Words: 0
Unique Insults Found:

None

User	Winning/Losing Splicing (Visual Grid)
Gigantour	I'm	playing	basketball	at	the	park.
Gigantour	The	park	is	sunny	and	the	sky	is	blue.	But	sometimes	the	park	is	rainy	and	the	sky	is	grey.
Gigantour	Its	amazing	Smoke.	Mountains	are	tall	and	difficult	to	climb.
Gigantour	Sorry.	I	know	it's	just	that	these	people	keep	asking	me	to	CLIMB	MOUNTAINS	when	they	barely	walk	outside	of	their	homes.
Gigantour	These	people	are	so	annoying	Smoke.

Summary Analysis:

WINNING DATA
Total Words: 0

No winning words detected.

LOSING DATA
Total Words: 0

No losing words detected.

User	Correctness / Incorrectness Splicing
Gigantour	I'm	playing	basketball	at	the	park.
Gigantour	The	park	is	sunny	and	the	sky	is	blue.	But	sometimes	the	park	is	rainy	and	the	sky	is	grey.
Gigantour	Its	amazing	Smoke.	Mountains	are	tall	and	difficult	to	climb.
Gigantour	Sorry.	I	know	it's	just	that	these	people	keep	asking	me	to	CLIMB	MOUNTAINS	when	they	barely	walk	outside	of	their	homes.
Gigantour	These	people	are	so	annoying	Smoke.

CORRECTNESS TOTAL: 0

None detected

INCORRECTNESS TOTAL: 0

None detected

GLOBAL INPUTS: PSYCH METRICS & BEHAVIORAL FILTERS

Core behavioral stats, sensitivity, credibility, and global ranking data.

3 Core Psych Stats
Metric	Positive / Corrective Count	Negative / Opposite Count	Total Words
1. Accuracy	Correctness: 5	Incorrectness: 4	9
2. Reliability	Winning: 19	Losing: 6	25
3. Social	Compliments: 30	Insults: 5	35

Global Inputs Sentiment Metrics
Comfort Score	Discomfort Score	Comfort + Discomfort Total	Total Word Count	Sentiment Ratio
280	-102	178.00	278	0.6403
Sentiment Algorithm: comfort score + discomfort score / divided by total word count. Discomfort remains negative.

Global Personality / IQ / Sensitivity Metrics
IQ1 = Total Unique Words	Total Feeling Words	Total Unique Feeling Words	Avg Sensitivity / Input
278	75	45	0.1120
Sensitivity Algorithm: total unique feeling words / divided by total unique word count.

Top 5 UN Behavioral Rankings
Top UN Accuracy & Reliability	Top UN Sensitivity Per Input
1. UN_DRBERKEN_YANK Corr: 1/0 = 100% // Win: 4/0 = 100% // Avg: 100% 2. UN_MEL_LISA Corr: 0/3 = 0% // Win: 2/0 = 100% // Avg: 50% 3. UN_FAB5SIXTHMAN_LISA Corr: 0/3 = 0% // Win: 2/0 = 100% // Avg: 50% 4. UN_GIGANTOUR_LISA Corr: 0/3 = 0% // Win: 2/0 = 100% // Avg: 50% 5. UN_FAB5SIXTHMAN_KRIS Corr: 0/1 = 0% // Win: 4/1 = 80% // Avg: 40%	1. Mel — 0.1369 2. Gigantour — 0.1269 3. Fab5sixthman — 0.1196 4. DrBerken — 0.0753 5. [Slot Open]

Global Usage / Memory Rankings
Most Unique Words Inputted (*IQ-1)	Most Inputs	Most Feeling Words Inputted	Most Unique Feeling Words	Most Conversations
Global Total: 278 1. DrBerken 144 2. Fab5sixthman 124 3. Gigantour 104 4. Mel 30 5. [Slot Open]	Global Total: 76 1. Fab5sixthman 27 2. DrBerken 20 3. Gigantour 19 4. Mel 10 5. [Slot Open]	Global Total: 75 1. Fab5sixthman 13 2. DrBerken 12 3. Gigantour 12 4. Mel 4 5. [Slot Open]	Global Total: 44 1. Gigantour 20 2. Fab5sixthman 19 3. DrBerken 10 4. Mel 5 5. [Slot Open]	Global Total: 15 1. Mel 4 2. Gigantour 4 3. Fab5sixthman 4 4. DrBerken 3 5. [Slot Open]

Behavioral Filter Definition: these metrics summarize global correctness, reliability, social feedback, sentiment, sensitivity, and usage behavior.

(Comfort + Discomfort Score) +2/-2 per Ego rank change	Facial Expression Output
20+	big smile and thumbs up
18+	bigger smile
16+	big smile
14+	smile
12+	blush with flowers
10+	blush
8+	wink and thumbs up
6+	wink and smirk
4+	smirk
0 to +2	thumbs up
-2 to 0	thumb down
-4 or lower	bummed
-6 or lower	preying
-8 or lower	stern frown
-10 or lower	mad yelling
-12 or lower	sick
-14 or lower	really sick
-16 or lower	sad
-18 or lower	teary eyed
-20 or lower	crying

User	Date	Input ID	Whole Input	Comfort + Discomfort Sum	Ego / Personality Rank Revision	Revised (Comfort+Discomfort) Score	Facial Output	How We Arrived There
Gigantour	2026-07-02 13:53:21	76	I'm (UN_Gigantour_SELF) playing basketball at the park.	4	+4 personality metric rose vs all UN's / 3rd parties	8	ID 11 Image: wink and thumbs up	comfort/discomfort sum 4 +4 personality metric revision = revised score 8, which maps to facial expression ID 11 — wink and thumbs up.
Gigantour	2026-07-02 13:52:34	75	The park is sunny (UN_Gigantour_sunny) and the sky is blue. But sometimes the park is rainy and the sky is grey.	2	-4 personality metric dropped vs all UN's / 3rd parties	-2	ID 5 Image: thumb down	comfort/discomfort sum 2 -4 personality metric revision = revised score -2, which maps to facial expression ID 5 — thumb down.
Gigantour	2026-07-02 13:51:21	74	Its amazing Smoke. Mountains are tall and difficult to climb.	8	+4 personality metric rose vs all UN's / 3rd parties	12	ID 21 Image: blush with flowers	comfort/discomfort sum 8 +4 personality metric revision = revised score 12, which maps to facial expression ID 21 — blush with flowers.
Gigantour	2026-07-02 13:50:17	73	Sorry. I (UN_Gigantour_SELF) know it's just that these people keep asking me (UN_Gigantour_SELF) to CLIMB MOUNTAINS when they (UN_Gigantour_SELF) barely walk outside of their homes.	2	+0 no ego-rank revision	2	ID 10 Image: thumbs up	comfort/discomfort sum 2 +0 personality metric revision = revised score 2, which maps to facial expression ID 10 — thumbs up.
Gigantour	2026-07-02 13:49:01	72	These people are so annoying Smoke.	-4	+0 no ego-rank revision	-4	ID 12 Image: bummed	comfort/discomfort sum -4 +0 personality metric revision = revised score -4, which maps to facial expression ID 12 — bummed.
Gigantour	2026-07-01 20:32:29	71	What moon phase are we in?	0	+4 personality metric rose vs all UN's / 3rd parties	4	ID 7 Image: smirk	comfort/discomfort sum 0 +4 personality metric revision = revised score 4, which maps to facial expression ID 7 — smirk.
Gigantour	2026-07-01 20:30:19	70	What time is it?	0	+4 personality metric rose vs all UN's / 3rd parties	4	ID 7 Image: smirk	comfort/discomfort sum 0 +4 personality metric revision = revised score 4, which maps to facial expression ID 7 — smirk.
Gigantour	2026-07-01 20:29:04	69	Harry (UN_Gigantour_harry) won the game.	6	+0 no ego-rank revision	6	ID 17 Image: wink and smirk	comfort/discomfort sum 6 +0 personality metric revision = revised score 6, which maps to facial expression ID 17 — wink and smirk.
Gigantour	2026-07-01 20:28:18	68	Winning is key. We're not perfect but we're improving.	12	+0 no ego-rank revision	12	ID 21 Image: blush with flowers	comfort/discomfort sum 12 +0 personality metric revision = revised score 12, which maps to facial expression ID 21 — blush with flowers.
Gigantour	2026-07-01 20:27:06	67	I (UN_Gigantour_SELF) was hanging out today by the soccer field. It was cold. But we (UN_Gigantour_SELF) won. Soccer is fun. Futball is fun. Football is fun.	16	+0 no ego-rank revision	16	ID 27 Image: big smile	comfort/discomfort sum 16 +0 personality metric revision = revised score 16, which maps to facial expression ID 27 — big smile.

PEOPLE — Global Persons + 3rd Parties

Total Global Persons + 3rd Parties Found: 17

#	Person / 3rd Party
1	UN_DRBERKEN
2	UN_DRBERKEN_KRIS
3	UN_DRBERKEN_YANK
4	UN_FAB5SIXTHMAN
5	UN_FAB5SIXTHMAN_DICK
6	UN_FAB5SIXTHMAN_KRIS
7	UN_FAB5SIXTHMAN_LISA
8	UN_FAB5SIXTHMAN_MAJOR
9	UN_FAB5SIXTHMAN_STANFORD
10	UN_GIGANTOUR
11	UN_GIGANTOUR_HARRY
12	UN_GIGANTOUR_JACKIE
13	UN_GIGANTOUR_LISA
14	UN_GIGANTOUR_SUNNY
15	UN_MEL
16	UN_MEL_KRIS
17	UN_MEL_LISA

ID: 76 | INPUT: I'm playing basketball at the park.

Machine Learning Formulas

Verb: none

[**S I'm (UN_Gigantour_SELF) playing basketball at] + [*S park.]

ID: 75 | INPUT: The park is sunny and the sky is blue. But sometimes the park is rainy and the sky is grey.

Machine Learning Formulas

Verb: none

[**S park is sunny (UN_Gigantour_sunny) and sky is] + [*S blue.] + [**S But sometimes park is rainy and sky is] + [*S grey.]

ID: 74 | INPUT: Its amazing Smoke. Mountains are tall and difficult to climb.

Machine Learning Formulas

Verb: climb

[**S Its amazing] + [*S Smoke.] + [**Q Mountains are tall and difficult] = [*PRESENT climb.] = ...

ID: 73 | INPUT: Sorry. I know it's just that these people keep asking me to CLIMB MOUNTAINS when they barely walk outside of their homes.

Machine Learning Formulas

Verb: know

[*S Sorry.] + [**Q I (UN_Gigantour_SELF)] = [*PRESENT know] = [**S it's just] + [*S these] + [**S people]

Verb: keep

[**S it's just] + [*S these] + [**S people] = [*PRESENT keep] = [**Q asking me (UN_Gigantour_SELF)]

Verb: climb

[**Q asking me (UN_Gigantour_SELF)] = [*PRESENT CLIMB] = [**Q MOUNTAINS when they (UN_Gigantour_SELF) barely]

Verb: walk

[**Q MOUNTAINS when they (UN_Gigantour_SELF) barely] = [*PRESENT walk] = [**S outside their] + [*S homes.]

ID: 72 | INPUT: These people are so annoying Smoke.

Machine Learning Formulas

Verb: none

[*S These] + [**Q people are] + [**S annoying] + [*S Smoke.]

Operative Word	Top 5 Usernames and UN_3rd Party's Associated With Word *Per Input
10x	#1 FAB5SIXTHMAN #2 FAB5SIXTHMAN #3 FAB5SIXTHMAN #4 FAB5SIXTHMAN #5 FAB5SIXTHMAN
150k	#1 FAB5SIXTHMAN #2 FAB5SIXTHMAN #3 FAB5SIXTHMAN #4 UN_FAB5SIXTHMAN_DICK #5 UN_FAB5SIXTHMAN_FAB5SIXTHMAN
40	#1 DRBERKEN #2 DRBERKEN #3 DRBERKEN #4 UN_DRBERKEN_DRBERKEN
about	#1 FAB5SIXTHMAN #2 FAB5SIXTHMAN #3 FAB5SIXTHMAN #4 FAB5SIXTHMAN #5 UN_FAB5SIXTHMAN_FAB5SIXTHMAN
accomplished	#1 MEL #2 MEL
act	#1 FAB5SIXTHMAN #2 FAB5SIXTHMAN #3 FAB5SIXTHMAN #4 FAB5SIXTHMAN #5 FAB5SIXTHMAN
actually	#1 DRBERKEN #2 DRBERKEN #3 UN_DRBERKEN_DRBERKEN
again	#1 FAB5SIXTHMAN #2 FAB5SIXTHMAN #3 DRBERKEN #4 DRBERKEN #5 DRBERKEN
agent	#1 DRBERKEN #2 DRBERKEN #3 UN_DRBERKEN_DRBERKEN
ai	#1 DRBERKEN #2 DRBERKEN #3 UN_DRBERKEN_DRBERKEN
aka	#1 GIGANTOUR #2 GIGANTOUR #3 GIGANTOUR #4 GIGANTOUR
albeit	#1 FAB5SIXTHMAN #2 UN_FAB5SIXTHMAN_MAJOR #3 FAB5SIXTHMAN
already	#1 FAB5SIXTHMAN #2 UN_FAB5SIXTHMAN_FAB5SIXTHMAN #3 FAB5SIXTHMAN #4 FAB5SIXTHMAN #5 FAB5SIXTHMAN
also	#1 DRBERKEN #2 DRBERKEN #3 DRBERKEN
amazing	#1 GIGANTOUR #2 GIGANTOUR
america	#1 GIGANTOUR #2 FAB5SIXTHMAN #3 UN_FAB5SIXTHMAN_FAB5SIXTHMAN #4 FAB5SIXTHMAN #5 FAB5SIXTHMAN
an	#1 DRBERKEN #2 DRBERKEN #3 DRBERKEN #4 DRBERKEN #5 UN_DRBERKEN_DRBERKEN
and	#1 GIGANTOUR #2 UN_DRBERKEN_DRBERKEN #3 FAB5SIXTHMAN #4 UN_FAB5SIXTHMAN_FAB5SIXTHMAN #5 FAB5SIXTHMAN
annoying	#1 GIGANTOUR #2 GIGANTOUR
answer	#1 UN_DRBERKEN_DRBERKEN #2 DRBERKEN #3 DRBERKEN #4 DRBERKEN #5 DRBERKEN
any	#1 UN_DRBERKEN_DRBERKEN #2 DRBERKEN #3 DRBERKEN #4 DRBERKEN #5 DRBERKEN
are	#1 GIGANTOUR #2 GIGANTOUR #3 DRBERKEN #4 MEL #5 FAB5SIXTHMAN
asked	#1 DRBERKEN #2 DRBERKEN #3 DRBERKEN #4 DRBERKEN
asking	#1 GIGANTOUR #2 GIGANTOUR #3 UN_GIGANTOUR_GIGANTOUR
asylum	#1 GIGANTOUR #2 GIGANTOUR #3 GIGANTOUR #4 GIGANTOUR
at	#1 FAB5SIXTHMAN #2 DRBERKEN #3 FAB5SIXTHMAN #4 FAB5SIXTHMAN #5 DRBERKEN
back	#1 DRBERKEN #2 DRBERKEN #3 DRBERKEN
bacon	#1 GIGANTOUR #2 GIGANTOUR #3 GIGANTOUR #4 GIGANTOUR #5 GIGANTOUR
ball	#1 DRBERKEN #2 DRBERKEN #3 DRBERKEN #4 UN_DRBERKEN_DRBERKEN
barely	#1 GIGANTOUR #2 GIGANTOUR #3 UN_GIGANTOUR_GIGANTOUR
baseball	#1 DRBERKEN #2 DRBERKEN #3 DRBERKEN #4 UN_DRBERKEN_DRBERKEN #5 DRBERKEN
basketball	#1 GIGANTOUR #2 UN_GIGANTOUR_GIGANTOUR
be	#1 DRBERKEN #2 DRBERKEN #3 DRBERKEN #4 UN_DRBERKEN_DRBERKEN #5 DRBERKEN
beach	#1 FAB5SIXTHMAN #2 FAB5SIXTHMAN #3 FAB5SIXTHMAN #4 FAB5SIXTHMAN #5 FAB5SIXTHMAN
been	#1 FAB5SIXTHMAN #2 UN_FAB5SIXTHMAN_STANFORD #3 FAB5SIXTHMAN #4 GIGANTOUR #5 UN_FAB5SIXTHMAN_FAB5SIXTHMAN
best	#1 DRBERKEN #2 DRBERKEN #3 DRBERKEN #4 UN_DRBERKEN_DRBERKEN #5 DRBERKEN
better	#1 FAB5SIXTHMAN #2 UN_FAB5SIXTHMAN_STANFORD #3 FAB5SIXTHMAN #4 DRBERKEN #5 UN_FAB5SIXTHMAN_FAB5SIXTHMAN
bit	#1 DRBERKEN #2 DRBERKEN #3 DRBERKEN #4 UN_DRBERKEN_DRBERKEN #5 DRBERKEN
blue	#1 GIGANTOUR #2 GIGANTOUR #3 UN_GIGANTOUR_SUNNY
boom	#1 GIGANTOUR #2 GIGANTOUR #3 GIGANTOUR #4 GIGANTOUR #5 GIGANTOUR
booya	#1 FAB5SIXTHMAN #2 FAB5SIXTHMAN #3 FAB5SIXTHMAN
breakfast	#1 GIGANTOUR #2 GIGANTOUR #3 GIGANTOUR #4 GIGANTOUR #5 GIGANTOUR
brunson	#1 DRBERKEN #2 DRBERKEN
bugs	#1 DRBERKEN #2 DRBERKEN #3 DRBERKEN #4 UN_DRBERKEN_DRBERKEN
but	#1 DRBERKEN #2 DRBERKEN #3 DRBERKEN #4 UN_GIGANTOUR_GIGANTOUR #5 DRBERKEN
by	#1 UN_GIGANTOUR_GIGANTOUR #2 GIGANTOUR #3 GIGANTOUR #4 GIGANTOUR
call	#1 FAB5SIXTHMAN #2 FAB5SIXTHMAN #3 UN_FAB5SIXTHMAN_FAB5SIXTHMAN #4 FAB5SIXTHMAN #5 FAB5SIXTHMAN
can	#1 DRBERKEN #2 DRBERKEN #3 DRBERKEN #4 UN_DRBERKEN_DRBERKEN #5 DRBERKEN
career	#1 DRBERKEN #2 DRBERKEN
chilling	#1 DRBERKEN #2 DRBERKEN #3 DRBERKEN #4 DRBERKEN #5 UN_DRBERKEN_DRBERKEN
cia	#1 DRBERKEN #2 DRBERKEN #3 UN_DRBERKEN_DRBERKEN
climb	#1 UN_GIGANTOUR_GIGANTOUR #2 GIGANTOUR #3 GIGANTOUR
coherent	#1 UN_FAB5SIXTHMAN_FAB5SIXTHMAN #2 FAB5SIXTHMAN #3 UN_FAB5SIXTHMAN_MAJOR #4 FAB5SIXTHMAN
cold	#1 UN_GIGANTOUR_GIGANTOUR #2 GIGANTOUR #3 GIGANTOUR #4 GIGANTOUR
coming	#1 DRBERKEN #2 DRBERKEN #3 DRBERKEN
convo	#1 DRBERKEN #2 DRBERKEN #3 DRBERKEN
cool	#1 GIGANTOUR #2 GIGANTOUR #3 GIGANTOUR #4 GIGANTOUR #5 GIGANTOUR
correctly	#1 UN_DRBERKEN_DRBERKEN #2 DRBERKEN #3 DRBERKEN #4 DRBERKEN #5 DRBERKEN
crazy	#1 MEL #2 MEL #3 MEL
currently	#1 FAB5SIXTHMAN #2 FAB5SIXTHMAN #3 FAB5SIXTHMAN #4 FAB5SIXTHMAN
day	#1 GIGANTOUR #2 UN_GIGANTOUR_GIGANTOUR #3 MEL #4 MEL #5 MEL
debug	#1 DRBERKEN #2 UN_DRBERKEN_DRBERKEN #3 DRBERKEN #4 DRBERKEN #5 DRBERKEN
deserved	#1 FAB5SIXTHMAN #2 FAB5SIXTHMAN #3 FAB5SIXTHMAN #4 FAB5SIXTHMAN #5 FAB5SIXTHMAN
dick	#1 FAB5SIXTHMAN #2 FAB5SIXTHMAN #3 FAB5SIXTHMAN #4 UN_FAB5SIXTHMAN_FAB5SIXTHMAN #5 FAB5SIXTHMAN
did	#1 FAB5SIXTHMAN #2 FAB5SIXTHMAN #3 FAB5SIXTHMAN #4 UN_FAB5SIXTHMAN_FAB5SIXTHMAN #5 FAB5SIXTHMAN
difficult	#1 GIGANTOUR #2 GIGANTOUR
disappointing	#1 FAB5SIXTHMAN #2 FAB5SIXTHMAN #3 FAB5SIXTHMAN #4 FAB5SIXTHMAN #5 FAB5SIXTHMAN
disc	#1 FAB5SIXTHMAN #2 FAB5SIXTHMAN #3 FAB5SIXTHMAN #4 FAB5SIXTHMAN #5 FAB5SIXTHMAN
dishes	#1 DRBERKEN #2 DRBERKEN
do	#1 DRBERKEN #2 FAB5SIXTHMAN #3 DRBERKEN #4 FAB5SIXTHMAN #5 FAB5SIXTHMAN
doing	#1 DRBERKEN #2 DRBERKEN #3 DRBERKEN #4 FAB5SIXTHMAN #5 DRBERKEN
dont	#1 UN_FAB5SIXTHMAN_DICK #2 FAB5SIXTHMAN #3 FAB5SIXTHMAN #4 FAB5SIXTHMAN #5 UN_FAB5SIXTHMAN_FAB5SIXTHMAN
earns	#1 FAB5SIXTHMAN #2 FAB5SIXTHMAN #3 FAB5SIXTHMAN #4 FAB5SIXTHMAN #5 UN_FAB5SIXTHMAN_FAB5SIXTHMAN
eggs	#1 GIGANTOUR #2 GIGANTOUR #3 GIGANTOUR #4 GIGANTOUR #5 GIGANTOUR
else	#1 DRBERKEN #2 DRBERKEN
even	#1 DRBERKEN #2 DRBERKEN
evening	#1 FAB5SIXTHMAN #2 FAB5SIXTHMAN #3 UN_FAB5SIXTHMAN_FAB5SIXTHMAN
every	#1 UN_FAB5SIXTHMAN_FAB5SIXTHMAN #2 FAB5SIXTHMAN #3 UN_FAB5SIXTHMAN_DICK #4 UN_FAB5SIXTHMAN_STANFORD #5 FAB5SIXTHMAN
exciting	#1 FAB5SIXTHMAN #2 FAB5SIXTHMAN
expect	#1 UN_DRBERKEN_DRBERKEN #2 DRBERKEN #3 DRBERKEN #4 DRBERKEN
facts	#1 DRBERKEN #2 DRBERKEN
failing	#1 DRBERKEN #2 UN_DRBERKEN_DRBERKEN #3 DRBERKEN #4 DRBERKEN #5 DRBERKEN
feel	#1 DRBERKEN #2 UN_FAB5SIXTHMAN_FAB5SIXTHMAN #3 FAB5SIXTHMAN #4 FAB5SIXTHMAN #5 DRBERKEN
feels	#1 FAB5SIXTHMAN #2 UN_FAB5SIXTHMAN_FAB5SIXTHMAN #3 FAB5SIXTHMAN #4 FAB5SIXTHMAN #5 FAB5SIXTHMAN
field	#1 GIGANTOUR #2 GIGANTOUR #3 UN_GIGANTOUR_GIGANTOUR #4 GIGANTOUR
floppy	#1 FAB5SIXTHMAN #2 FAB5SIXTHMAN #3 FAB5SIXTHMAN #4 FAB5SIXTHMAN #5 FAB5SIXTHMAN
football	#1 GIGANTOUR #2 GIGANTOUR #3 UN_GIGANTOUR_GIGANTOUR #4 GIGANTOUR
for	#1 GIGANTOUR #2 GIGANTOUR #3 GIGANTOUR #4 GIGANTOUR #5 GIGANTOUR
frustrating	#1 FAB5SIXTHMAN #2 UN_FAB5SIXTHMAN_MAJOR #3 FAB5SIXTHMAN
fun	#1 GIGANTOUR #2 GIGANTOUR #3 GIGANTOUR #4 UN_GIGANTOUR_GIGANTOUR
functional	#1 UN_DRBERKEN_DRBERKEN #2 DRBERKEN #3 DRBERKEN
further	#1 DRBERKEN #2 DRBERKEN #3 DRBERKEN
futball	#1 GIGANTOUR #2 GIGANTOUR #3 GIGANTOUR #4 UN_GIGANTOUR_GIGANTOUR
game	#1 FAB5SIXTHMAN #2 DRBERKEN #3 UN_GIGANTOUR_JACKIE #4 GIGANTOUR #5 FAB5SIXTHMAN
going	#1 FAB5SIXTHMAN #2 FAB5SIXTHMAN #3 FAB5SIXTHMAN #4 FAB5SIXTHMAN
good	#1 DRBERKEN #2 FAB5SIXTHMAN #3 UN_FAB5SIXTHMAN_FAB5SIXTHMAN #4 FAB5SIXTHMAN #5 FAB5SIXTHMAN
got	#1 DRBERKEN #2 DRBERKEN #3 FAB5SIXTHMAN #4 FAB5SIXTHMAN #5 FAB5SIXTHMAN
graduate	#1 FAB5SIXTHMAN #2 UN_FAB5SIXTHMAN_STANFORD #3 FAB5SIXTHMAN #4 UN_FAB5SIXTHMAN_FAB5SIXTHMAN #5 FAB5SIXTHMAN
great	#1 UN_GIGANTOUR_LISA #2 UN_GIGANTOUR_JACKIE #3 GIGANTOUR #4 GIGANTOUR #5 GIGANTOUR
grey	#1 GIGANTOUR #2 GIGANTOUR #3 UN_GIGANTOUR_SUNNY
hanging	#1 DRBERKEN #2 DRBERKEN #3 GIGANTOUR #4 DRBERKEN #5 DRBERKEN
happy	#1 FAB5SIXTHMAN #2 FAB5SIXTHMAN #3 UN_FAB5SIXTHMAN_FAB5SIXTHMAN #4 FAB5SIXTHMAN #5 FAB5SIXTHMAN
harry	#1 GIGANTOUR #2 GIGANTOUR #3 GIGANTOUR #4 UN_GIGANTOUR_HARRY
having	#1 GIGANTOUR #2 GIGANTOUR #3 GIGANTOUR #4 GIGANTOUR #5 GIGANTOUR
hey	#1 DRBERKEN #2 DRBERKEN #3 DRBERKEN #4 GIGANTOUR #5 MEL
his	#1 DRBERKEN #2 DRBERKEN
home	#1 FAB5SIXTHMAN #2 FAB5SIXTHMAN #3 UN_FAB5SIXTHMAN_FAB5SIXTHMAN #4 FAB5SIXTHMAN #5 FAB5SIXTHMAN
homes	#1 UN_GIGANTOUR_GIGANTOUR #2 GIGANTOUR #3 GIGANTOUR
hospital	#1 FAB5SIXTHMAN #2 FAB5SIXTHMAN #3 UN_FAB5SIXTHMAN_FAB5SIXTHMAN #4 FAB5SIXTHMAN #5 FAB5SIXTHMAN
house	#1 MEL #2 UN_MEL_MEL #3 MEL #4 MEL #5 UN_MEL_LISA
huge	#1 DRBERKEN #2 DRBERKEN
human	#1 DRBERKEN #2 DRBERKEN #3 DRBERKEN #4 DRBERKEN #5 UN_DRBERKEN_DRBERKEN
if	#1 DRBERKEN #2 DRBERKEN #3 DRBERKEN #4 DRBERKEN #5 UN_DRBERKEN_DRBERKEN
im	#1 GIGANTOUR #2 UN_GIGANTOUR_SUNNY #3 UN_GIGANTOUR_GIGANTOUR
improving	#1 GIGANTOUR #2 GIGANTOUR #3 GIGANTOUR
in	#1 GIGANTOUR #2 GIGANTOUR #3 FAB5SIXTHMAN #4 DRBERKEN #5 DRBERKEN
incredibly	#1 FAB5SIXTHMAN #2 FAB5SIXTHMAN #3 UN_FAB5SIXTHMAN_FAB5SIXTHMAN #4 FAB5SIXTHMAN #5 FAB5SIXTHMAN
industry	#1 DRBERKEN #2 DRBERKEN
input	#1 DRBERKEN #2 DRBERKEN #3 DRBERKEN #4 UN_DRBERKEN_DRBERKEN
invented	#1 FAB5SIXTHMAN #2 FAB5SIXTHMAN #3 FAB5SIXTHMAN #4 FAB5SIXTHMAN #5 FAB5SIXTHMAN
is	#1 FAB5SIXTHMAN #2 DRBERKEN #3 DRBERKEN #4 FAB5SIXTHMAN #5 DRBERKEN
it	#1 DRBERKEN #2 DRBERKEN #3 GIGANTOUR #4 GIGANTOUR #5 FAB5SIXTHMAN
its	#1 DRBERKEN #2 DRBERKEN #3 DRBERKEN #4 GIGANTOUR #5 GIGANTOUR
jackie	#1 UN_GIGANTOUR_LISA #2 UN_GIGANTOUR_JACKIE #3 GIGANTOUR #4 GIGANTOUR #5 GIGANTOUR
jalen	#1 DRBERKEN #2 DRBERKEN
just	#1 UN_GIGANTOUR_GIGANTOUR #2 DRBERKEN #3 UN_DRBERKEN_DRBERKEN #4 FAB5SIXTHMAN #5 FAB5SIXTHMAN
keep	#1 UN_GIGANTOUR_GIGANTOUR #2 DRBERKEN #3 GIGANTOUR #4 GIGANTOUR #5 DRBERKEN
key	#1 GIGANTOUR #2 GIGANTOUR #3 GIGANTOUR
knicks	#1 GIGANTOUR #2 GIGANTOUR #3 GIGANTOUR #4 GIGANTOUR #5 GIGANTOUR
know	#1 FAB5SIXTHMAN #2 UN_DRBERKEN_DRBERKEN #3 UN_GIGANTOUR_GIGANTOUR #4 FAB5SIXTHMAN #5 DRBERKEN
knows	#1 FAB5SIXTHMAN #2 FAB5SIXTHMAN #3 FAB5SIXTHMAN #4 FAB5SIXTHMAN #5 FAB5SIXTHMAN
kris	#1 MEL #2 FAB5SIXTHMAN #3 FAB5SIXTHMAN #4 UN_FAB5SIXTHMAN_LISA #5 UN_DRBERKEN_KRIS
learning	#1 UN_DRBERKEN_DRBERKEN #2 DRBERKEN #3 DRBERKEN #4 DRBERKEN
like	#1 DRBERKEN #2 FAB5SIXTHMAN #3 FAB5SIXTHMAN #4 UN_DRBERKEN_DRBERKEN #5 FAB5SIXTHMAN
linked	#1 DRBERKEN #2 DRBERKEN #3 DRBERKEN #4 DRBERKEN
lisa	#1 MEL #2 UN_MEL_LISA #3 UN_FAB5SIXTHMAN_LISA #4 FAB5SIXTHMAN #5 UN_FAB5SIXTHMAN_KRIS
long	#1 GIGANTOUR #2 GIGANTOUR #3 GIGANTOUR
look	#1 DRBERKEN #2 FAB5SIXTHMAN #3 FAB5SIXTHMAN #4 FAB5SIXTHMAN #5 DRBERKEN
looking	#1 DRBERKEN #2 DRBERKEN
losing	#1 FAB5SIXTHMAN #2 FAB5SIXTHMAN #3 FAB5SIXTHMAN #4 FAB5SIXTHMAN
lost	#1 UN_FAB5SIXTHMAN_FAB5SIXTHMAN #2 FAB5SIXTHMAN #3 UN_FAB5SIXTHMAN_KRIS #4 DRBERKEN #5 UN_DRBERKEN_DRBERKEN
machine	#1 DRBERKEN #2 DRBERKEN #3 UN_DRBERKEN_DRBERKEN #4 DRBERKEN
mad	#1 FAB5SIXTHMAN #2 UN_FAB5SIXTHMAN_FAB5SIXTHMAN #3 FAB5SIXTHMAN #4 FAB5SIXTHMAN #5 FAB5SIXTHMAN
magic	#1 DRBERKEN #2 DRBERKEN #3 UN_DRBERKEN_DRBERKEN #4 DRBERKEN
major	#1 UN_FAB5SIXTHMAN_MAJOR #2 UN_FAB5SIXTHMAN_FAB5SIXTHMAN #3 FAB5SIXTHMAN #4 FAB5SIXTHMAN
makes	#1 UN_FAB5SIXTHMAN_FAB5SIXTHMAN #2 FAB5SIXTHMAN #3 UN_FAB5SIXTHMAN_DICK #4 FAB5SIXTHMAN #5 FAB5SIXTHMAN
making	#1 DRBERKEN #2 DRBERKEN
math	#1 DRBERKEN #2 DRBERKEN #3 UN_DRBERKEN_DRBERKEN #4 DRBERKEN #5 DRBERKEN
me	#1 FAB5SIXTHMAN #2 FAB5SIXTHMAN #3 UN_FAB5SIXTHMAN_FAB5SIXTHMAN #4 FAB5SIXTHMAN #5 FAB5SIXTHMAN
mind	#1 FAB5SIXTHMAN #2 FAB5SIXTHMAN #3 FAB5SIXTHMAN #4 FAB5SIXTHMAN #5 FAB5SIXTHMAN
missing	#1 DRBERKEN #2 UN_DRBERKEN_DRBERKEN #3 DRBERKEN #4 DRBERKEN
mission	#1 MEL #2 MEL
ml	#1 DRBERKEN #2 DRBERKEN #3 DRBERKEN #4 UN_DRBERKEN_DRBERKEN #5 DRBERKEN
module	#1 DRBERKEN #2 DRBERKEN #3 DRBERKEN #4 UN_DRBERKEN_DRBERKEN #5 DRBERKEN
money	#1 UN_FAB5SIXTHMAN_FAB5SIXTHMAN #2 FAB5SIXTHMAN #3 FAB5SIXTHMAN #4 FAB5SIXTHMAN #5 FAB5SIXTHMAN
moon	#1 MEL #2 MEL #3 FAB5SIXTHMAN #4 MEL #5 FAB5SIXTHMAN
mountains	#1 GIGANTOUR #2 UN_GIGANTOUR_GIGANTOUR #3 GIGANTOUR
my	#1 UN_FAB5SIXTHMAN_FAB5SIXTHMAN #2 FAB5SIXTHMAN #3 FAB5SIXTHMAN #4 UN_MEL_LISA #5 MEL
nature	#1 DRBERKEN #2 UN_DRBERKEN_DRBERKEN #3 DRBERKEN
need	#1 DRBERKEN #2 DRBERKEN #3 DRBERKEN #4 UN_DRBERKEN_DRBERKEN #5 DRBERKEN
new	#1 GIGANTOUR #2 GIGANTOUR #3 UN_GIGANTOUR_GIGANTOUR #4 GIGANTOUR #5 GIGANTOUR
night	#1 FAB5SIXTHMAN #2 UN_FAB5SIXTHMAN_DICK #3 UN_FAB5SIXTHMAN_FAB5SIXTHMAN #4 FAB5SIXTHMAN #5 FAB5SIXTHMAN
no	#1 FAB5SIXTHMAN #2 UN_FAB5SIXTHMAN_FAB5SIXTHMAN #3 FAB5SIXTHMAN #4 FAB5SIXTHMAN #5 FAB5SIXTHMAN
not	#1 GIGANTOUR #2 GIGANTOUR #3 GIGANTOUR
off	#1 GIGANTOUR #2 GIGANTOUR #3 GIGANTOUR #4 DRBERKEN #5 UN_GIGANTOUR_GIGANTOUR
old	#1 FAB5SIXTHMAN #2 FAB5SIXTHMAN #3 FAB5SIXTHMAN #4 FAB5SIXTHMAN #5 FAB5SIXTHMAN
only	#1 FAB5SIXTHMAN #2 FAB5SIXTHMAN #3 FAB5SIXTHMAN #4 UN_FAB5SIXTHMAN_FAB5SIXTHMAN #5 FAB5SIXTHMAN
or	#1 FAB5SIXTHMAN #2 FAB5SIXTHMAN #3 FAB5SIXTHMAN #4 FAB5SIXTHMAN #5 UN_FAB5SIXTHMAN_MAJOR
other	#1 FAB5SIXTHMAN #2 FAB5SIXTHMAN #3 FAB5SIXTHMAN #4 UN_FAB5SIXTHMAN_DICK #5 UN_FAB5SIXTHMAN_FAB5SIXTHMAN
out	#1 DRBERKEN #2 GIGANTOUR #3 GIGANTOUR #4 GIGANTOUR #5 DRBERKEN
outside	#1 GIGANTOUR #2 GIGANTOUR #3 UN_GIGANTOUR_GIGANTOUR
own	#1 FAB5SIXTHMAN #2 FAB5SIXTHMAN #3 FAB5SIXTHMAN #4 UN_FAB5SIXTHMAN_FAB5SIXTHMAN #5 FAB5SIXTHMAN
park	#1 UN_DRBERKEN_DRBERKEN #2 DRBERKEN #3 GIGANTOUR #4 UN_GIGANTOUR_SUNNY #5 DRBERKEN
past	#1 DRBERKEN #2 DRBERKEN #3 DRBERKEN #4 UN_DRBERKEN_DRBERKEN #5 UN_DRBERKEN_KRIS
pennhurst	#1 GIGANTOUR #2 GIGANTOUR #3 GIGANTOUR #4 GIGANTOUR
people	#1 FAB5SIXTHMAN #2 FAB5SIXTHMAN #3 FAB5SIXTHMAN #4 FAB5SIXTHMAN #5 GIGANTOUR
perfect	#1 GIGANTOUR #2 GIGANTOUR #3 GIGANTOUR
phase	#1 FAB5SIXTHMAN #2 MEL #3 MEL #4 FAB5SIXTHMAN #5 FAB5SIXTHMAN
pissed	#1 GIGANTOUR #2 GIGANTOUR #3 GIGANTOUR #4 UN_GIGANTOUR_GIGANTOUR #5 GIGANTOUR
played	#1 GIGANTOUR #2 UN_GIGANTOUR_LISA #3 UN_GIGANTOUR_JACKIE #4 GIGANTOUR #5 GIGANTOUR
playing	#1 UN_GIGANTOUR_GIGANTOUR #2 GIGANTOUR
precision	#1 UN_DRBERKEN_DRBERKEN #2 DRBERKEN #3 DRBERKEN #4 DRBERKEN
pretty	#1 FAB5SIXTHMAN #2 UN_FAB5SIXTHMAN_MAJOR #3 FAB5SIXTHMAN #4 UN_FAB5SIXTHMAN_FAB5SIXTHMAN
problems	#1 UN_DRBERKEN_DRBERKEN #2 DRBERKEN #3 DRBERKEN #4 DRBERKEN #5 DRBERKEN
question	#1 UN_DRBERKEN_DRBERKEN #2 DRBERKEN #3 DRBERKEN #4 DRBERKEN #5 DRBERKEN
rainy	#1 UN_GIGANTOUR_SUNNY #2 GIGANTOUR #3 GIGANTOUR
random	#1 DRBERKEN #2 UN_DRBERKEN_DRBERKEN #3 DRBERKEN #4 DRBERKEN #5 DRBERKEN
refine	#1 DRBERKEN #2 UN_DRBERKEN_DRBERKEN #3 DRBERKEN #4 DRBERKEN
responses	#1 FAB5SIXTHMAN #2 UN_FAB5SIXTHMAN_MAJOR #3 FAB5SIXTHMAN #4 UN_FAB5SIXTHMAN_FAB5SIXTHMAN
satisfying	#1 FAB5SIXTHMAN #2 FAB5SIXTHMAN #3 FAB5SIXTHMAN #4 FAB5SIXTHMAN #5 FAB5SIXTHMAN
see	#1 UN_FAB5SIXTHMAN_FAB5SIXTHMAN #2 FAB5SIXTHMAN #3 UN_FAB5SIXTHMAN_MAJOR #4 FAB5SIXTHMAN #5 FAB5SIXTHMAN
semi	#1 UN_FAB5SIXTHMAN_FAB5SIXTHMAN #2 FAB5SIXTHMAN #3 UN_FAB5SIXTHMAN_MAJOR #4 FAB5SIXTHMAN
she	#1 UN_FAB5SIXTHMAN_FAB5SIXTHMAN #2 GIGANTOUR #3 UN_GIGANTOUR_LISA #4 FAB5SIXTHMAN #5 UN_FAB5SIXTHMAN_DICK
shelter	#1 GIGANTOUR #2 GIGANTOUR #3 GIGANTOUR #4 GIGANTOUR #5 UN_GIGANTOUR_GIGANTOUR
should	#1 FAB5SIXTHMAN #2 FAB5SIXTHMAN #3 UN_FAB5SIXTHMAN_FAB5SIXTHMAN #4 FAB5SIXTHMAN #5 FAB5SIXTHMAN
sister	#1 UN_FAB5SIXTHMAN_FAB5SIXTHMAN #2 UN_FAB5SIXTHMAN_DICK #3 FAB5SIXTHMAN #4 FAB5SIXTHMAN #5 FAB5SIXTHMAN
skipped	#1 DRBERKEN #2 DRBERKEN #3 DRBERKEN
sky	#1 GIGANTOUR #2 UN_GIGANTOUR_SUNNY #3 GIGANTOUR
smoke	#1 GIGANTOUR #2 DRBERKEN #3 MEL #4 UN_FAB5SIXTHMAN_FAB5SIXTHMAN #5 MEL
soccer	#1 GIGANTOUR #2 GIGANTOUR #3 GIGANTOUR #4 UN_GIGANTOUR_GIGANTOUR
solve	#1 DRBERKEN #2 UN_DRBERKEN_DRBERKEN #3 DRBERKEN #4 DRBERKEN #5 DRBERKEN
something	#1 DRBERKEN #2 DRBERKEN #3 UN_DRBERKEN_DRBERKEN #4 DRBERKEN #5 DRBERKEN
sometimes	#1 FAB5SIXTHMAN #2 GIGANTOUR #3 FAB5SIXTHMAN #4 GIGANTOUR #5 MEL
sorry	#1 UN_GIGANTOUR_GIGANTOUR #2 GIGANTOUR #3 GIGANTOUR
stanford	#1 FAB5SIXTHMAN #2 FAB5SIXTHMAN #3 FAB5SIXTHMAN #4 UN_FAB5SIXTHMAN_FAB5SIXTHMAN #5 UN_FAB5SIXTHMAN_STANFORD
stellar	#1 FAB5SIXTHMAN #2 FAB5SIXTHMAN #3 FAB5SIXTHMAN
still	#1 DRBERKEN #2 DRBERKEN #3 DRBERKEN
sucks	#1 FAB5SIXTHMAN #2 FAB5SIXTHMAN #3 UN_FAB5SIXTHMAN_FAB5SIXTHMAN #4 UN_FAB5SIXTHMAN_DICK #5 FAB5SIXTHMAN
sunny	#1 GIGANTOUR #2 GIGANTOUR #3 UN_GIGANTOUR_SUNNY
tad	#1 DRBERKEN #2 DRBERKEN #3 UN_DRBERKEN_DRBERKEN #4 DRBERKEN #5 DRBERKEN
tall	#1 GIGANTOUR #2 GIGANTOUR
taught	#1 DRBERKEN #2 DRBERKEN #3 DRBERKEN #4 DRBERKEN
teach	#1 DRBERKEN #2 DRBERKEN #3 UN_DRBERKEN_DRBERKEN #4 DRBERKEN #5 DRBERKEN
team	#1 DRBERKEN #2 DRBERKEN #3 DRBERKEN #4 DRBERKEN #5 UN_DRBERKEN_DRBERKEN
than	#1 FAB5SIXTHMAN #2 FAB5SIXTHMAN #3 FAB5SIXTHMAN #4 FAB5SIXTHMAN #5 UN_FAB5SIXTHMAN_FAB5SIXTHMAN
their	#1 UN_GIGANTOUR_GIGANTOUR #2 GIGANTOUR #3 GIGANTOUR
then	#1 DRBERKEN #2 DRBERKEN #3 DRBERKEN #4 DRBERKEN #5 UN_DRBERKEN_DRBERKEN
they	#1 FAB5SIXTHMAN #2 FAB5SIXTHMAN #3 UN_GIGANTOUR_GIGANTOUR #4 DRBERKEN #5 DRBERKEN
thing	#1 FAB5SIXTHMAN #2 FAB5SIXTHMAN #3 FAB5SIXTHMAN #4 FAB5SIXTHMAN #5 FAB5SIXTHMAN
things	#1 DRBERKEN #2 DRBERKEN #3 FAB5SIXTHMAN #4 DRBERKEN #5 DRBERKEN
though	#1 DRBERKEN #2 DRBERKEN #3 DRBERKEN #4 UN_DRBERKEN_DRBERKEN #5 DRBERKEN
through	#1 FAB5SIXTHMAN #2 FAB5SIXTHMAN #3 FAB5SIXTHMAN #4 FAB5SIXTHMAN #5 FAB5SIXTHMAN
time	#1 GIGANTOUR #2 UN_GIGANTOUR_SUNNY #3 GIGANTOUR #4 GIGANTOUR
today	#1 UN_GIGANTOUR_GIGANTOUR #2 GIGANTOUR #3 DRBERKEN #4 DRBERKEN #5 MEL
tonight	#1 FAB5SIXTHMAN #2 FAB5SIXTHMAN #3 FAB5SIXTHMAN #4 FAB5SIXTHMAN
unknowing	#1 DRBERKEN #2 DRBERKEN #3 DRBERKEN #4 DRBERKEN #5 UN_DRBERKEN_DRBERKEN
un_drberken_kris	#1 UN_DRBERKEN_KRIS #2 DRBERKEN
un_drberken_self	#1 DRBERKEN #2 DRBERKEN #3 DRBERKEN #4 DRBERKEN #5 UN_DRBERKEN_DRBERKEN
un_drberken_yank	#1 DRBERKEN #2 DRBERKEN #3 DRBERKEN #4 UN_DRBERKEN_DRBERKEN #5 DRBERKEN
un_fab5sixthman_dick	#1 FAB5SIXTHMAN #2 FAB5SIXTHMAN #3 FAB5SIXTHMAN #4 FAB5SIXTHMAN #5 UN_FAB5SIXTHMAN_DICK
un_fab5sixthman_kris	#1 FAB5SIXTHMAN #2 UN_FAB5SIXTHMAN_LISA #3 UN_FAB5SIXTHMAN_KRIS #4 FAB5SIXTHMAN #5 FAB5SIXTHMAN
un_fab5sixthman_lisa	#1 UN_FAB5SIXTHMAN_LISA #2 UN_FAB5SIXTHMAN_KRIS #3 FAB5SIXTHMAN
un_fab5sixthman_major	#1 FAB5SIXTHMAN #2 UN_FAB5SIXTHMAN_MAJOR #3 UN_FAB5SIXTHMAN_FAB5SIXTHMAN #4 FAB5SIXTHMAN
un_fab5sixthman_self	#1 FAB5SIXTHMAN #2 FAB5SIXTHMAN #3 FAB5SIXTHMAN #4 FAB5SIXTHMAN #5 UN_FAB5SIXTHMAN_FAB5SIXTHMAN
un_fab5sixthman_stanford	#1 FAB5SIXTHMAN #2 FAB5SIXTHMAN #3 FAB5SIXTHMAN #4 FAB5SIXTHMAN #5 UN_FAB5SIXTHMAN_STANFORD
un_gigantour_harry	#1 GIGANTOUR #2 GIGANTOUR #3 UN_GIGANTOUR_HARRY #4 GIGANTOUR
un_gigantour_jackie	#1 GIGANTOUR #2 GIGANTOUR #3 UN_GIGANTOUR_LISA #4 UN_GIGANTOUR_JACKIE #5 GIGANTOUR
un_gigantour_lisa	#1 GIGANTOUR #2 GIGANTOUR #3 UN_GIGANTOUR_LISA #4 UN_GIGANTOUR_JACKIE #5 GIGANTOUR
un_gigantour_self	#1 UN_GIGANTOUR_GIGANTOUR #2 GIGANTOUR #3 GIGANTOUR #4 GIGANTOUR #5 GIGANTOUR
un_gigantour_sunny	#1 GIGANTOUR #2 UN_GIGANTOUR_SUNNY #3 GIGANTOUR
un_mel_kris	#1 MEL #2 MEL #3 UN_MEL_KRIS
un_mel_lisa	#1 UN_MEL_LISA #2 MEL #3 MEL #4 UN_MEL_MEL #5 MEL
un_mel_self	#1 UN_MEL_LISA #2 MEL #3 MEL #4 UN_MEL_MEL #5 MEL
up	#1 DRBERKEN #2 DRBERKEN #3 DRBERKEN #4 DRBERKEN #5 DRBERKEN
v2	#1 DRBERKEN #2 DRBERKEN
v3	#1 DRBERKEN #2 DRBERKEN #3 DRBERKEN
walk	#1 GIGANTOUR #2 UN_GIGANTOUR_GIGANTOUR #3 GIGANTOUR
was	#1 FAB5SIXTHMAN #2 UN_FAB5SIXTHMAN_FAB5SIXTHMAN #3 UN_MEL_MEL #4 MEL #5 UN_DRBERKEN_DRBERKEN
wash	#1 DRBERKEN #2 DRBERKEN
watching	#1 UN_DRBERKEN_DRBERKEN #2 DRBERKEN #3 DRBERKEN #4 DRBERKEN #5 DRBERKEN
we	#1 GIGANTOUR #2 GIGANTOUR #3 FAB5SIXTHMAN #4 MEL #5 GIGANTOUR
were	#1 GIGANTOUR #2 GIGANTOUR #3 GIGANTOUR #4 GIGANTOUR #5 GIGANTOUR
what	#1 FAB5SIXTHMAN #2 DRBERKEN #3 DRBERKEN #4 FAB5SIXTHMAN #5 FAB5SIXTHMAN
whats	#1 DRBERKEN #2 DRBERKEN #3 DRBERKEN #4 DRBERKEN #5 DRBERKEN
when	#1 DRBERKEN #2 DRBERKEN #3 GIGANTOUR #4 FAB5SIXTHMAN #5 GIGANTOUR
who	#1 FAB5SIXTHMAN #2 DRBERKEN #3 UN_DRBERKEN_DRBERKEN #4 FAB5SIXTHMAN #5 FAB5SIXTHMAN
win	#1 MEL #2 FAB5SIXTHMAN #3 FAB5SIXTHMAN #4 UN_FAB5SIXTHMAN_FAB5SIXTHMAN #5 DRBERKEN
winning	#1 FAB5SIXTHMAN #2 GIGANTOUR #3 FAB5SIXTHMAN #4 GIGANTOUR #5 GIGANTOUR
won	#1 DRBERKEN #2 DRBERKEN #3 FAB5SIXTHMAN #4 FAB5SIXTHMAN #5 FAB5SIXTHMAN
working	#1 FAB5SIXTHMAN #2 FAB5SIXTHMAN #3 FAB5SIXTHMAN #4 FAB5SIXTHMAN #5 UN_FAB5SIXTHMAN_FAB5SIXTHMAN
worthwhile	#1 FAB5SIXTHMAN #2 FAB5SIXTHMAN #3 FAB5SIXTHMAN #4 FAB5SIXTHMAN #5 UN_FAB5SIXTHMAN_FAB5SIXTHMAN
would	#1 DRBERKEN #2 DRBERKEN #3 UN_DRBERKEN_DRBERKEN #4 DRBERKEN #5 DRBERKEN
wrong	#1 MEL #2 UN_MEL_MEL #3 DRBERKEN #4 MEL #5 GIGANTOUR
wundervar	#1 FAB5SIXTHMAN #2 FAB5SIXTHMAN
yanks	#1 DRBERKEN #2 DRBERKEN #3 DRBERKEN #4 DRBERKEN #5 DRBERKEN
year	#1 FAB5SIXTHMAN #2 FAB5SIXTHMAN #3 FAB5SIXTHMAN #4 UN_FAB5SIXTHMAN_FAB5SIXTHMAN #5 UN_FAB5SIXTHMAN_DICK
yesterday	#1 MEL #2 MEL #3 UN_MEL_MEL #4 MEL #5 FAB5SIXTHMAN
yet	#1 FAB5SIXTHMAN #2 FAB5SIXTHMAN #3 FAB5SIXTHMAN #4 FAB5SIXTHMAN #5 UN_FAB5SIXTHMAN_FAB5SIXTHMAN
york	#1 GIGANTOUR #2 UN_GIGANTOUR_GIGANTOUR #3 GIGANTOUR #4 GIGANTOUR #5 GIGANTOUR
you	#1 FAB5SIXTHMAN #2 FAB5SIXTHMAN #3 DRBERKEN #4 DRBERKEN #5 DRBERKEN
your	#1 FAB5SIXTHMAN #2 DRBERKEN #3 DRBERKEN #4 FAB5SIXTHMAN #5 UN_FAB5SIXTHMAN_FAB5SIXTHMAN

Matrix Logic:

Each operative word stores the highest-ranked persons/names and UN's associated with that word in inputs globally (*All UN's inputs).

Example:
game → UN_GIGANTOUR_KRIS
win → GIGANTOUR
kris → UN_GIGANTOUR_KRIS

This creates a global person ↔ skill/subject association matrix that can later be used for personality, ego, reputation, subject expertise, and skill-building calculations.

EGO Formula (*Global Inputs only)

Formula	Knowledge (IQ1)	Ego
Ego = 1 / IQ1 or Knowledge (*unique word count - global inputs only)	296	0.00337838

GLOBAL INPUTS: AI MORALITY SECTOR

Weighted Subject Skill Scores: 0, 2, 4, 6, 8, 10

Subject Skill Graduation Scale
Jargon 0	Subject 2+	Concept 4+	Idea 6+	Skill 8+	Master Skill 10

Morality Metric	Formula / Meaning	Current Global Value
Base Global Morality	Average subject skill score across all of the UN & UN_3rd party's subject skill tables. All subject skill level's witnessed (3rd party's) and observed of the UN's themselves, averaged. UN morality tables counted:* 4	2.52
Lowly Morality	Lowest morality average among all UN morality tables and all UN 3rd-party skill-building weighted averages.	UN: Mel — 1.81
Good Morality	Highest morality average among all UN morality tables and all UN 3rd-party skill-building weighted averages.	3rd Party: Drberken / UN: DrBerken — 4.24
Ideal Morality	Highest morality average witnessed plus 10 Master Skill.	3rd Party: Drberken / UN: DrBerken — 4.24 + 10 Master Skill
Divine Morality	Base global morality multiplied by infinity.	2.52 * Infinity /// Base Global Morality * Infinity

Morality Sector Definition: morality is displayed as the average subject skill witnessed across all UN morality tables and all 3rd-party skill-building averages.

Subject	Global UN Inputs Only	Guest Inputs Only	Global Robot Responses Only	Global Inputs + Robot Responses	Guest Robot Responses Only	Guest Inputs + Robot Responses	Convergence Avg	Spread	Agreement %	POVs Found
a	—	—	8.00	8.00	—	—	8.00	0.00	100.00%	2 / 6
now	—	—	8.00	8.00	—	—	8.00	0.00	100.00%	2 / 6
un_drberken_self	8.00	—	8.00	7.50	—	—	7.83	0.24	95.20%	3 / 6
an	7.00	—	8.00	7.67	—	—	7.56	0.42	91.60%	3 / 6
be	6.67	—	—	7.33	—	—	7.00	0.33	93.40%	2 / 6
have	—	—	7.00	7.00	—	—	7.00	0.00	100.00%	2 / 6
i	—	—	7.00	7.00	—	—	7.00	0.00	100.00%	2 / 6
in	5.82	—	8.00	6.44	—	—	6.75	0.92	81.60%	3 / 6
to	—	—	6.50	6.50	—	—	6.50	0.00	100.00%	2 / 6
do	4.80	—	8.00	5.29	—	—	6.03	1.41	71.80%	3 / 6
as	—	—	6.00	6.00	—	—	6.00	0.00	100.00%	2 / 6
data	—	—	6.00	6.00	—	—	6.00	0.00	100.00%	2 / 6
enough	—	—	6.00	6.00	—	—	6.00	0.00	100.00%	2 / 6
on	—	—	6.00	6.00	—	—	6.00	0.00	100.00%	2 / 6
sounds	—	—	6.00	6.00	—	—	6.00	0.00	100.00%	2 / 6
what	4.57	—	8.00	5.39	—	—	5.99	1.46	70.80%	3 / 6
past	5.33	—	—	6.40	—	—	5.87	0.54	89.20%	2 / 6
un_fab5sixthman_self	5.33	—	—	6.18	—	—	5.76	0.43	91.40%	2 / 6
where	—	—	5.75	5.75	—	—	5.75	0.00	100.00%	2 / 6
is	4.78	—	6.80	5.65	—	—	5.74	0.83	83.40%	3 / 6
we	4.50	—	7.00	5.07	—	—	5.52	1.07	78.60%	3 / 6
talking	—	—	5.50	5.50	—	—	5.50	0.00	100.00%	2 / 6
and	4.00	—	8.00	4.40	—	—	5.47	1.80	64.00%	3 / 6
self	—	—	5.33	5.33	—	—	5.33	0.00	100.00%	2 / 6
are	4.25	—	6.80	4.82	—	—	5.29	1.09	78.20%	3 / 6
or	4.50	—	6.00	5.25	—	—	5.25	0.61	87.80%	3 / 6
at	5.00	—	—	5.48	—	—	5.24	0.24	95.20%	2 / 6
me	4.57	—	6.00	5.08	—	—	5.22	0.59	88.20%	3 / 6
ai	5.00	—	—	5.33	—	—	5.17	0.17	96.60%	2 / 6
not	4.00	—	6.00	5.33	—	—	5.11	0.83	83.40%	3 / 6
un_gigantour_self	6.00	—	4.00	5.00	—	—	5.00	0.82	83.60%	3 / 6
un_drberken_yank	5.00	—	5.00	5.00	—	—	5.00	0.00	100.00%	3 / 6
thought	—	—	5.00	5.00	—	—	5.00	0.00	100.00%	2 / 6
yank	—	—	5.00	5.00	—	—	5.00	0.00	100.00%	2 / 6
you	4.33	—	6.00	4.44	—	—	4.92	0.76	84.80%	3 / 6
it	5.43	—	4.00	5.18	—	—	4.87	0.62	87.60%	3 / 6
was	4.14	—	5.75	4.46	—	—	4.78	0.70	86.00%	3 / 6
out	4.00	—	6.00	4.17	—	—	4.72	0.91	81.80%	3 / 6
about	4.00	—	5.50	4.60	—	—	4.70	0.62	87.60%	3 / 6
who	4.00	—	5.43	4.56	—	—	4.66	0.59	88.20%	3 / 6
yanks	5.00	—	4.00	4.75	—	—	4.58	0.42	91.60%	3 / 6
im	4.67	—	4.50	4.57	—	—	4.58	0.07	98.60%	3 / 6
game	4.00	—	5.50	4.24	—	—	4.58	0.66	86.80%	3 / 6
random	4.00	—	5.00	4.55	—	—	4.52	0.41	91.80%	3 / 6
win	4.00	—	5.33	4.24	—	—	4.52	0.58	88.40%	3 / 6
its	4.67	—	4.00	4.86	—	—	4.51	0.37	92.60%	3 / 6
when	4.00	—	5.20	4.33	—	—	4.51	0.51	89.80%	3 / 6
know	4.00	—	5.00	4.21	—	—	4.40	0.43	91.40%	3 / 6
my	4.67	—	4.00	4.46	—	—	4.38	0.28	94.40%	3 / 6
won	4.17	—	4.67	4.19	—	—	4.34	0.23	95.40%	3 / 6
answer	4.00	—	4.67	4.25	—	—	4.31	0.28	94.40%	3 / 6
can	4.00	—	4.67	4.25	—	—	4.31	0.28	94.40%	3 / 6
but	4.29	—	4.00	4.33	—	—	4.21	0.15	97.00%	3 / 6
10x	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
150k	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
40	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
accomplished	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
act	4.00	—	4.00	4.00	—	—	4.00	0.00	100.00%	3 / 6
actually	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
again	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
agent	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
aka	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
albeit	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
already	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
also	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
amazing	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
america	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
annoying	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
any	4.00	—	4.00	4.00	—	—	4.00	0.00	100.00%	3 / 6
asked	4.00	—	4.00	4.00	—	—	4.00	0.00	100.00%	3 / 6
asking	4.00	—	4.00	4.00	—	—	4.00	0.00	100.00%	3 / 6
asylum	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
back	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
bacon	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
ball	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
barely	4.00	—	4.00	4.00	—	—	4.00	0.00	100.00%	3 / 6
baseball	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
basketball	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
beach	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
been	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
best	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
better	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
bit	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
blue	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
boom	4.00	—	4.00	4.00	—	—	4.00	0.00	100.00%	3 / 6
booya	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
breakfast	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
brunson	4.00	—	4.00	4.00	—	—	4.00	0.00	100.00%	3 / 6
bugs	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
by	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
call	4.00	—	4.00	4.00	—	—	4.00	0.00	100.00%	3 / 6
career	4.00	—	4.00	4.00	—	—	4.00	0.00	100.00%	3 / 6
chilling	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
cia	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
climb	4.00	—	4.00	4.00	—	—	4.00	0.00	100.00%	3 / 6
coherent	4.00	—	4.00	4.00	—	—	4.00	0.00	100.00%	3 / 6
cold	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
coming	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
convo	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
cool	4.00	—	4.00	4.00	—	—	4.00	0.00	100.00%	3 / 6
correctly	4.00	—	4.00	4.00	—	—	4.00	0.00	100.00%	3 / 6
crazy	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
currently	4.00	—	4.00	4.00	—	—	4.00	0.00	100.00%	3 / 6
day	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
debug	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
deserved	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
dick	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
did	4.00	—	4.00	4.00	—	—	4.00	0.00	100.00%	3 / 6
difficult	4.00	—	4.00	4.00	—	—	4.00	0.00	100.00%	3 / 6
disappointing	4.00	—	4.00	4.00	—	—	4.00	0.00	100.00%	3 / 6
disc	4.00	—	4.00	4.00	—	—	4.00	0.00	100.00%	3 / 6
dishes	4.00	—	4.00	4.00	—	—	4.00	0.00	100.00%	3 / 6
doing	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
dont	4.00	—	4.00	4.00	—	—	4.00	0.00	100.00%	3 / 6
earns	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
eggs	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
else	4.00	—	4.00	4.00	—	—	4.00	0.00	100.00%	3 / 6
even	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
evening	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
every	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
exciting	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
expect	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
facts	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
failing	4.00	—	4.00	4.00	—	—	4.00	0.00	100.00%	3 / 6
feel	4.00	—	4.00	4.00	—	—	4.00	0.00	100.00%	3 / 6
feels	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
field	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
floppy	4.00	—	4.00	4.00	—	—	4.00	0.00	100.00%	3 / 6
football	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
for	4.00	—	4.00	4.00	—	—	4.00	0.00	100.00%	3 / 6
frustrating	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
fun	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
functional	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
further	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
futball	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
going	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
good	4.00	—	4.00	4.00	—	—	4.00	0.00	100.00%	3 / 6
got	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
graduate	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
great	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
grey	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
hanging	4.00	—	4.00	4.00	—	—	4.00	0.00	100.00%	3 / 6
happy	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
harry	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
having	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
hey	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
his	4.00	—	4.00	4.00	—	—	4.00	0.00	100.00%	3 / 6
home	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
homes	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
hospital	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
house	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
huge	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
human	4.00	—	4.00	4.00	—	—	4.00	0.00	100.00%	3 / 6
if	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
improving	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
incredibly	4.00	—	4.00	4.00	—	—	4.00	0.00	100.00%	3 / 6
industry	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
input	4.00	—	4.00	4.00	—	—	4.00	0.00	100.00%	3 / 6
invented	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
jackie	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
jalen	4.00	—	4.00	4.00	—	—	4.00	0.00	100.00%	3 / 6
just	4.00	—	4.00	4.00	—	—	4.00	0.00	100.00%	3 / 6
keep	4.00	—	4.00	4.00	—	—	4.00	0.00	100.00%	3 / 6
key	4.00	—	4.00	4.00	—	—	4.00	0.00	100.00%	3 / 6
knicks	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
knows	4.00	—	4.00	4.00	—	—	4.00	0.00	100.00%	3 / 6
kris	4.00	—	4.00	4.00	—	—	4.00	0.00	100.00%	3 / 6
learning	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
like	4.00	—	4.00	4.00	—	—	4.00	0.00	100.00%	3 / 6
linked	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
lisa	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
long	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
look	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
looking	4.00	—	4.00	4.00	—	—	4.00	0.00	100.00%	3 / 6
losing	4.00	—	4.00	4.00	—	—	4.00	0.00	100.00%	3 / 6
lost	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
machine	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
mad	4.00	—	4.00	4.00	—	—	4.00	0.00	100.00%	3 / 6
magic	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
major	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
makes	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
making	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
math	4.00	—	4.00	4.00	—	—	4.00	0.00	100.00%	3 / 6
mind	4.00	—	4.00	4.00	—	—	4.00	0.00	100.00%	3 / 6
missing	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
mission	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
ml	4.00	—	4.00	4.00	—	—	4.00	0.00	100.00%	3 / 6
module	4.00	—	4.00	4.00	—	—	4.00	0.00	100.00%	3 / 6
money	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
moon	4.00	—	4.00	4.00	—	—	4.00	0.00	100.00%	3 / 6
mountains	4.00	—	4.00	4.00	—	—	4.00	0.00	100.00%	3 / 6
nature	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
need	4.00	—	4.00	4.00	—	—	4.00	0.00	100.00%	3 / 6
new	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
night	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
no	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
off	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
old	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
only	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
other	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
outside	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
own	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
park	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
pennhurst	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
people	4.00	—	4.00	4.00	—	—	4.00	0.00	100.00%	3 / 6
perfect	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
phase	4.00	—	4.00	4.00	—	—	4.00	0.00	100.00%	3 / 6
pissed	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
played	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
playing	4.00	—	4.00	4.00	—	—	4.00	0.00	100.00%	3 / 6
precision	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
pretty	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
problems	4.00	—	4.00	4.00	—	—	4.00	0.00	100.00%	3 / 6
question	4.00	—	4.00	4.00	—	—	4.00	0.00	100.00%	3 / 6
rainy	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
refine	4.00	—	4.00	4.00	—	—	4.00	0.00	100.00%	3 / 6
responses	4.00	—	4.00	4.00	—	—	4.00	0.00	100.00%	3 / 6
robot	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
satisfying	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
see	4.00	—	4.00	4.00	—	—	4.00	0.00	100.00%	3 / 6
semi	4.00	—	4.00	4.00	—	—	4.00	0.00	100.00%	3 / 6
she	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
shelter	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
should	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
sister	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
skipped	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
sky	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
smoke	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
soccer	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
solve	4.00	—	4.00	4.00	—	—	4.00	0.00	100.00%	3 / 6
something	4.00	—	4.00	4.00	—	—	4.00	0.00	100.00%	3 / 6
sometimes	4.00	—	4.00	4.00	—	—	4.00	0.00	100.00%	3 / 6
sorry	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
stanford	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
stellar	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
still	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
sucks	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
sunny	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
tad	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
tall	4.00	—	4.00	4.00	—	—	4.00	0.00	100.00%	3 / 6
taught	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
teach	4.00	—	4.00	4.00	—	—	4.00	0.00	100.00%	3 / 6
team	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
than	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
their	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
then	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
they	4.00	—	4.00	4.00	—	—	4.00	0.00	100.00%	3 / 6
thing	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
things	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
though	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
through	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
time	4.00	—	4.00	4.00	—	—	4.00	0.00	100.00%	3 / 6
today	4.00	—	4.00	4.00	—	—	4.00	0.00	100.00%	3 / 6
tonight	4.00	—	4.00	4.00	—	—	4.00	0.00	100.00%	3 / 6
unknowing	4.00	—	4.00	4.00	—	—	4.00	0.00	100.00%	3 / 6
un_drberken_kris	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
un_fab5sixthman_dick	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
un_fab5sixthman_kris	4.00	—	4.00	4.00	—	—	4.00	0.00	100.00%	3 / 6
un_fab5sixthman_lisa	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
un_fab5sixthman_major	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
un_fab5sixthman_stanford	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
un_gigantour_harry	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
un_gigantour_jackie	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
un_gigantour_lisa	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
un_gigantour_sunny	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
un_mel_kris	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
un_mel_lisa	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
un_mel_self	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
up	4.00	—	4.00	4.00	—	—	4.00	0.00	100.00%	3 / 6
v2	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
v3	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
walk	4.00	—	4.00	4.00	—	—	4.00	0.00	100.00%	3 / 6
wash	4.00	—	4.00	4.00	—	—	4.00	0.00	100.00%	3 / 6
watching	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
were	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
whats	4.00	—	4.00	4.00	—	—	4.00	0.00	100.00%	3 / 6
winning	4.00	—	4.00	4.00	—	—	4.00	0.00	100.00%	3 / 6
working	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
worthwhile	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
would	4.00	—	4.00	4.00	—	—	4.00	0.00	100.00%	3 / 6
wrong	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
wundervar	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
year	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
yesterday	4.00	—	4.00	4.00	—	—	4.00	0.00	100.00%	3 / 6
yet	4.00	—	4.00	4.00	—	—	4.00	0.00	100.00%	3 / 6
york	4.00	—	—	4.00	—	—	4.00	0.00	100.00%	2 / 6
your	4.00	—	4.00	4.00	—	—	4.00	0.00	100.00%	3 / 6
1	—	—	4.00	4.00	—	—	4.00	0.00	100.00%	2 / 6
12	—	—	4.00	4.00	—	—	4.00	0.00	100.00%	2 / 6
78	—	—	4.00	4.00	—	—	4.00	0.00	100.00%	2 / 6
above	—	—	4.00	4.00	—	—	4.00	0.00	100.00%	2 / 6
accurate	—	—	4.00	4.00	—	—	4.00	0.00	100.00%	2 / 6
affection	—	—	4.00	4.00	—	—	4.00	0.00	100.00%	2 / 6
aunts	—	—	4.00	4.00	—	—	4.00	0.00	100.00%	2 / 6
boring	—	—	4.00	4.00	—	—	4.00	0.00	100.00%	2 / 6
cant	—	—	4.00	4.00	—	—	4.00	0.00	100.00%	2 / 6
chillin	—	—	4.00	4.00	—	—	4.00	0.00	100.00%	2 / 6
cleaner	—	—	4.00	4.00	—	—	4.00	0.00	100.00%	2 / 6
composed	—	—	4.00	4.00	—	—	4.00	0.00	100.00%	2 / 6
current	—	—	4.00	4.00	—	—	4.00	0.00	100.00%	2 / 6
daylight	—	—	4.00	4.00	—	—	4.00	0.00	100.00%	2 / 6
days	—	—	4.00	4.00	—	—	4.00	0.00	100.00%	2 / 6
drberken	—	—	4.00	4.00	—	—	4.00	0.00	100.00%	2 / 6
easier	—	—	4.00	4.00	—	—	4.00	0.00	100.00%	2 / 6
eat	—	—	4.00	4.00	—	—	4.00	0.00	100.00%	2 / 6
exhausted	—	—	4.00	4.00	—	—	4.00	0.00	100.00%	2 / 6
feelings	—	—	4.00	4.00	—	—	4.00	0.00	100.00%	2 / 6
friday	—	—	4.00	4.00	—	—	4.00	0.00	100.00%	2 / 6
function	—	—	4.00	4.00	—	—	4.00	0.00	100.00%	2 / 6
gibbous	—	—	4.00	4.00	—	—	4.00	0.00	100.00%	2 / 6
goal	—	—	4.00	4.00	—	—	4.00	0.00	100.00%	2 / 6
horizon	—	—	4.00	4.00	—	—	4.00	0.00	100.00%	2 / 6
illuminated	—	—	4.00	4.00	—	—	4.00	0.00	100.00%	2 / 6
loving	—	—	4.00	4.00	—	—	4.00	0.00	100.00%	2 / 6
mood	—	—	4.00	4.00	—	—	4.00	0.00	100.00%	2 / 6
number	—	—	4.00	4.00	—	—	4.00	0.00	100.00%	2 / 6
percent	—	—	4.00	4.00	—	—	4.00	0.00	100.00%	2 / 6
personal	—	—	4.00	4.00	—	—	4.00	0.00	100.00%	2 / 6
possess	—	—	4.00	4.00	—	—	4.00	0.00	100.00%	2 / 6
provide	—	—	4.00	4.00	—	—	4.00	0.00	100.00%	2 / 6
require	—	—	4.00	4.00	—	—	4.00	0.00	100.00%	2 / 6
right	—	—	4.00	4.00	—	—	4.00	0.00	100.00%	2 / 6
savings	—	—	4.00	4.00	—	—	4.00	0.00	100.00%	2 / 6
seductively	—	—	4.00	4.00	—	—	4.00	0.00	100.00%	2 / 6
sleep	—	—	4.00	4.00	—	—	4.00	0.00	100.00%	2 / 6
stands	—	—	4.00	4.00	—	—	4.00	0.00	100.00%	2 / 6
starts	—	—	4.00	4.00	—	—	4.00	0.00	100.00%	2 / 6
statement	—	—	4.00	4.00	—	—	4.00	0.00	100.00%	2 / 6
stq	—	—	4.00	4.00	—	—	4.00	0.00	100.00%	2 / 6
sun	—	—	4.00	4.00	—	—	4.00	0.00	100.00%	2 / 6
the	—	—	4.00	4.00	—	—	4.00	0.00	100.00%	2 / 6
tired	—	—	4.00	4.00	—	—	4.00	0.00	100.00%	2 / 6
too	—	—	4.00	4.00	—	—	4.00	0.00	100.00%	2 / 6
toxins	—	—	4.00	4.00	—	—	4.00	0.00	100.00%	2 / 6
waxing	—	—	4.00	4.00	—	—	4.00	0.00	100.00%	2 / 6

Convergence Key
Convergence Avg	Average morality score for that subject across available POVs.
Spread	How far apart the POV scores are. Lower = more converged.
Agreement %	Estimated POV agreement. Higher = stronger morality convergence.

Metric ID	Psych Metric Name	Definition
IQ Sector
1	IQ 1 — Global Inputs - Total Unique Words	Total unique operative words identified within the UN's conversation history.
2	IQ 2 — Global Inputs - Avg of all UN's Subject Skills	Average skill level across all subjects identified in the UN's skill-building data.
3	IQ 3 — Global Inputs - Win / Correctness + Past Tense Verb Formula	Measures demonstrated success, correctness, and proven action formulas witnessed through past-tense behavioral patterns.
Morality Sector
4	Morality 1 — Global Inputs - Base Morality Peers	Average subject skill level witnessed across all UN's and 3rd parties.
5	Morality 2 — Global Inputs - Highest Avg Skill	Highest average subject skill level achieved by the logged-in UN.
6	Morality 3 — Global Inputs - Peak Subject Seen	Highest subject skill level witnessed across the logged-in UN and associated 3rd parties.
7	Morality 4 — Global Inputs - Lowest Subject Seen	Lowest subject skill level witnessed across the logged-in UN and associated 3rd parties.
Formula Note: Personality Formula Ranks currently apply to individual UN's and are not calculated from the global aggregate.

GLOBAL INPUTS: USER METRICS + PERSONALITY FORMULA

Personality = IQ + Morality

User / Peer Metrics
Total UN's	Total 3rd Parties	Total Peers	Total Inputs
4	13	17	76
Total Conversations	Avg Words / Input	Avg Inputs / Conversation	Avg Conversations / Input
15	9.0921	5.07	0.1972

Emotional Learning + Subconscious Metrics
Avg Feeling Words / Input	Avg Sensitivity / Input	Avg Sentiment / Input	Ego
0.9737	0.1120 Feeling words / total words	0.2945 Comfort v Discomfort / total words	0.003597 1 / IQ1
Self Esteem (Total Comfort+Discomfort sum)	Comfort Score Total	Discomfort Score Total	IQ1 = Knowledge
178	280	-102	278 Total unique words and jargon

Personality Formula: IQ + Morality
Metric ID	Psych Metric Name	Global Stat Value
1	IQ 1 — Global Inputs - Total Unique Words	278
2	IQ 2 — Global Inputs - Avg of all UN's Subject Skills	4.54
3	IQ 3 — Global Inputs - Win / Correctness + Past Tense Verb Formula	23
Morality Sector
4	Morality 1 — Global Inputs - Base Morality Peers: avg subject skill all UN's + 3rd parties	4.29
5	Morality 2 — Global Inputs - Highest Avg Skill, UN only	DrBerken (4.39)
6	Morality 3 — Global Inputs - Peak Subject Seen, UN + 3rd parties	DrBerken-an-Level 4: Skill
7	Morality 4 — Global Inputs - Lowest Subject Seen, UN + 3rd parties	DrBerken-your-Level 2: Concept

Formula Note: Personality formula ranks currently apply to UN's, not the global aggregate.

POV	Database	Table	Total ---(ML 2) Linkages	Total Emotional Rationale Linkages	Total Logical Rationale Linkages	UN With The Most ML 2 Linkages	Top 5 UNs (most ML 2 linkages)	Distinct STQ Pairs (statements and questions)
Global Inputs Only = POV	Ai2STQ1_ML	Ai2_ML_2_rationale_sureness	1,740	758	982	DrBerken 997 linkages	1. DrBerken — 997 2. Fab5sixthman — 475 3. Gigantour — 258 4. Mel — 10	1,740
UN Specific Inputs Only = POV	Ai2STQ1_ML	UN_Guest_Ai2_ML_2_rationale_sureness Table not found yet	0	0	0	null	null	0
Global Inputs + Global Robot Responses = POV	Ai2STQ1_ML_Robot	Robot_and_UN_global_Ai2_ML_2_rationale_sureness	4,122	1,996	2,126	DrBerken 1,890 linkages	1. DrBerken — 1,890 2. Fab5sixthman — 1,213 3. Gigantour — 942 4. Mel — 77	4,122
UN Specific Inputs + UN Specific Robot Responses = POV	Ai2STQ1_ML_Robot	Guest_Robot_and_UN_global_Ai2_ML_2_rationale_sureness Table not found yet	0	0	0	null	null	0

Convergence Metric	Value	Meaning
POVs With Data	2 / 4	How many of the four ML Module 2 POV tables currently contain linkage-pair data.
Shared Pairs Across All 4 POVs	0	STQ linkage pairs that appear in every POV.
Shared Pairs Across 3+ POVs	0	Strong convergence: linkage pairs appearing in at least three POVs.
Shared Pairs Across 2+ POVs	0	Partial convergence: linkage pairs appearing in at least two POVs.
4-POV Convergence %	0%	Shared-all-4 pairs divided by the largest distinct-pair count from any active POV.

Rank	UN	Combined Linkage Count
1	DrBerken	2,887
2	Fab5sixthman	1,688
3	Gigantour	1,200
4	Mel	87

#	Emotion Category	Meaning
1	Happy / Positive	Raw joy, happiness, pleasure, smile, comfort.
2	Sad / Negative	Crying, emotions, burdens, pain, suffering.
3	Regretful / Introspective	Doubt, fear, caution, hesitation, regrets.
4	Inspired / Inquisitive	Skills, beginning, goals, peers, friends, relationships.
5	Motivated By...	Finishing, winning, admiration, compliments, achievement.
6	Unmotivated By...	Losing, insults, boredom, redundancy, repetition.
7	Physical Exhaustion	Fatigue, depletion, burnout, tiredness, low energy.

Input ID	UN	Input	Feeling Words Found	Emotion Categories In Input
67	Gigantour Jul 02, 2026 3:26 AM	I was hanging out today by the soccer field. It was cold. But we won. Soccer is fun. Futball is fun. Football is fun.	won [5], fun [4], cold [7]	5. Motivated By... 4. Inspired / Inquisitive 7. Physical Exhaustion
68	Gigantour Jul 02, 2026 3:28 AM	Winning is key. We're not perfect but we're improving.	winning [5], perfect [5]	5. Motivated By...
69	Gigantour Jul 02, 2026 3:28 AM	Harry won the game.	won [5]	5. Motivated By...
70	Gigantour Jul 02, 2026 3:30 AM	What time is it?	null	null
71	Gigantour Jul 02, 2026 3:32 AM	What moon phase are we in?	null	null
72	Gigantour Jul 02, 2026 8:48 PM	These people are so annoying Smoke.	annoying [2]	2. Sad / Negative
73	Gigantour Jul 02, 2026 8:49 PM	Sorry. I know it's just that these people keep asking me to CLIMB MOUNTAINS when they barely walk outside of their homes.	homes [1], walk [7], sorry [3]	1. Happy / Positive 7. Physical Exhaustion 3. Regretful / Introspective
74	Gigantour Jul 02, 2026 8:50 PM	Its amazing Smoke. Mountains are tall and difficult to climb.	amazing [5], difficult [3]	5. Motivated By... 3. Regretful / Introspective
75	Gigantour Jul 02, 2026 8:52 PM	The park is sunny and the sky is blue. But sometimes the park is rainy and the sky is grey.	sunny [1]	1. Happy / Positive
76	Gigantour Jul 02, 2026 8:53 PM	I'm playing basketball at the park.	playing [4]	4. Inspired / Inquisitive

UN: Gigantour

"These people are so annoying Smoke." (2. Sad / Negative) → "Sorry. I know it's just that these people keep asking me to CLIMB MOUNTAINS when..." (1. Happy / Positive + 7. Physical Exhaustion + 3. Regretful / Introspective) → "Its amazing Smoke. Mountains are tall and difficult to climb." (5. Motivated By... + 3. Regretful / Introspective) → "The park is sunny and the sky is blue. But sometimes the park is rainy and the s..." (1. Happy / Positive) → "I'm playing basketball at the park." (4. Inspired / Inquisitive)

Emotion Category 1 - WORD CLOUD

Happy / Positive

homes (1) accomplished (1) good (1) house (1) happy (1) home (1) sunny (1)

Emotion Category 2 - WORD CLOUD

Sad / Negative

annoying (1) pissed (1) bugs (1)

Emotion Category 3 - WORD CLOUD

Regretful / Introspective

mad (1) difficult (1) sorry (1)

Emotion Category 4 - WORD CLOUD

Inspired / Inquisitive

fun (1) sister (1) played (1) disappointing (1) playing (1) frustrating (1)

Emotion Category 5 - WORD CLOUD

Motivated By...

perfect (1) winning (1) great (1) won (1) incredibly (1) amazing (1) pretty (1) earns (1) cool (1) exciting (1) win (1) best (1) correctly (1)

Emotion Category 6 - WORD CLOUD

Unmotivated By...

crazy (1) dick (1) failing (1) losing (1) lost (1)

Emotion Category 7 - WORD CLOUD

Physical Exhaustion

cold (1) breakfast (1) walk (1)

LLM Global Comfort / Discomfort Totals
All UN Comfort Sum	278
All UN Discomfort Sum	-106
All UN Comfort + Discomfort Total Sum	172

#	UN	Total Inputs	Total Words	Comfort Words Hit	Comfort Sum	% of LLM Comfort	Discomfort Words Hit	Discomfort Sum	% of LLM Discomfort	Comfort + Discomfort Total Sum	% of LLM Total
1	Fab5sixthman	27	206	19	114	41.01%	8	-40	37.74%	74	43.02%
2	Gigantour	19	163	20	94	33.81%	6	-24	22.64%	70	40.7%
3	DrBerken	20	263	9	54	19.42%	8	-34	32.08%	20	11.63%
4	Mel	10	35	3	16	5.76%	2	-8	7.55%	8	4.65%

#	UN	Unanswered Question	Response	Answered By	Answer Type
1	Gigantour	Mountains are tall and difficult	As to (Mountains are tall and difficult)-- We are currently on input number 1..	Module 3 - Machine Learning	Intellectual
2	Gigantour	CLIMB MOUNTAINS when they (UN_Gigantour_SELF) barely walk	As to (CLIMB MOUNTAINS when they (UN_Gigantour_SELF) barely walk) -- I do not have enough data on that.	Module 3 - Machine Learning	N/A
3	Gigantour	keep asking me (UN_Gigantour_SELF)	As to (keep asking me (UN_Gigantour_SELF)) -- I do not have enough data on that.	Module 3 - Machine Learning	Conversational
4	Gigantour	people are	Iâ€™m not in the mood to answer something like (people are) right now.	Module 10 - Exhaustion / Free Will	N/A
5	Gigantour	What moon phase are we in ?	As to (What moon phase are we in ?)-- The current moon phase is Waxing Gibbous..	Module 3 - Machine Learning	N/A
6	Gigantour	What time is it ?	As to (What time is it ?)-- Daylight Savings Time starts in 12 days..	Module 3 - Machine Learning	N/A
7	Gigantour	game	As to (game)-- Winning is key.	Module 3 - Machine Learning	Intellectual
8	Gigantour	game	As to (game)-- boom.	Module 3 - Machine Learning	Intellectual
9	Gigantour	game	As to (game)-- cool.	Module 3 - Machine Learning	Intellectual
10	DrBerken	game	As to (game)-- refine.	Module 3 - Machine Learning	Intellectual

Cognitive Response Statistics
Machine Learning - Module 3 (Logic/Emotion linkages) Answered X # of questions	45
Machine Learning - Module 10 (Free Will/Exhaustion) Answered X # of questions	5
Cognitive/Thinking or Reasoning Response Types
Confirmational	0% (0)
Intellectual	44.4% (8)
Conversational	50% (9)
Problem Solving	5.6% (1)

#	Person	Correctness / Winning / Credibility Stats
1	UN_FAB5SIXTHMAN	Corr: 0/0 = 0% // Win: 0/0 = 0% // Avg: 0%
2	UN_FAB5SIXTHMAN_KRIS	Corr: 0/1 = 0% // Win: 4/1 = 80% // Avg: 40%
3	UN_FAB5SIXTHMAN_STANFORD	Corr: 0/0 = 0% // Win: 0/1 = 0% // Avg: 0%
4	UN_FAB5SIXTHMAN_DICK	Corr: 0/0 = 0% // Win: 1/1 = 50% // Avg: 25%
5	UN_FAB5SIXTHMAN_MAJOR	Corr: 0/0 = 0% // Win: 1/0 = 100% // Avg: 50%
6	UN_MEL	Corr: 0/0 = 0% // Win: 0/0 = 0% // Avg: 0%
7	UN_MEL_LISA	Corr: 0/3 = 0% // Win: 2/0 = 100% // Avg: 50%
8	UN_MEL_KRIS	Corr: 0/1 = 0% // Win: 4/1 = 80% // Avg: 40%
9	UN_FAB5SIXTHMAN_LISA	Corr: 0/3 = 0% // Win: 2/0 = 100% // Avg: 50%
10	UN_DRBERKEN	Corr: 0/0 = 0% // Win: 0/0 = 0% // Avg: 0%
11	UN_DRBERKEN_YANK	Corr: 1/0 = 100% // Win: 4/0 = 100% // Avg: 100%
12	UN_DRBERKEN_KRIS	Corr: 0/1 = 0% // Win: 4/1 = 80% // Avg: 40%
13	UN_GIGANTOUR	Corr: 0/0 = 0% // Win: 0/0 = 0% // Avg: 0%
14	UN_GIGANTOUR_JACKIE	Corr: 0/1 = 0% // Win: 1/0 = 100% // Avg: 50%
15	UN_GIGANTOUR_LISA	Corr: 0/3 = 0% // Win: 2/0 = 100% // Avg: 50%
16	UN_GIGANTOUR_HARRY	Corr: 0/0 = 0% // Win: 1/0 = 100% // Avg: 50%
17	UN_GIGANTOUR_SUNNY	Corr: 0/0 = 0% // Win: 0/0 = 0% // Avg: 0%

Total Response-Type Activations
70 Total Robot Inputs With Response Types
Neural Module / Response Type	Frequency of Activation	% of Total Inputs
response_1_id_confirmations.php	14 hits	20%
response_3_logical.php	6 hits	8.57%
response_1_id_confirmations.php, response_3_logical.php	6 hits	8.57%
response_1_id_confirmations.php, response_8_personality_warping.php	5 hits	7.14%
response_3_logical.php, response_5_TEMPEROL_LOBE_history.php	3 hits	4.29%
response_1_id_confirmations.php, response_9_imaginative.php	3 hits	4.29%
response_8_personality_warping.php	3 hits	4.29%
response_1_id_confirmations.php, response_4_emotional.php, response_3_logical.php, response_5_TEMPEROL_LOBE_history.php	2 hits	2.86%
response_1_id_confirmations.php, response_4_emotional.php	2 hits	2.86%
response_1_id_confirmations.php, response_3_logical.php, response_5_TEMPEROL_LOBE_history.php	2 hits	2.86%
response_5_TEMPEROL_LOBE_history.php	2 hits	2.86%
response_1_id_confirmations.php, response_10_free_will.php	2 hits	2.86%
response_3_logical.php, response_8_personality_warping.php	2 hits	2.86%
response_4_emotional.php	2 hits	2.86%
response_4_emotional.php, response_3_logical.php, response_5_TEMPEROL_LOBE_history.php, response_8_personality_warping.php	2 hits	2.86%
response_1_id_confirmations.php, response_5_TEMPEROL_LOBE_history.php, response_8_personality_warping.php	1 hits	1.43%
response_9_imaginative.php	1 hits	1.43%
response_3_logical.php, response_5_TEMPEROL_LOBE_history.php, response_8_personality_warping.php	1 hits	1.43%
response_1_id_confirmations.php, response_10_free_will.php, response_3_logical.php	1 hits	1.43%
response_4_emotional.php, response_3_logical.php	1 hits	1.43%
response_3_logical.php, response_5_TEMPEROL_LOBE_history.php, response_9_imaginative.php	1 hits	1.43%
response_3_logical.php, response_10_free_will.php, response_8_personality_warping.php	1 hits	1.43%
response_1_id_confirmations.php, response_3_logical.php, response_5_TEMPEROL_LOBE_history.php, response_8_personality_warping.php	1 hits	1.43%
response_1_id_confirmations.php, response_4_emotional.php, response_3_logical.php, response_8_personality_warping.php	1 hits	1.43%
response_3_logical.php, response_9_imaginative.php	1 hits	1.43%
response_1_id_confirmations.php, response_10_free_will.php, response_5_TEMPEROL_LOBE_history.php	1 hits	1.43%
response_1_id_confirmations.php, response_4_emotional.php, response_5_TEMPEROL_LOBE_history.php	1 hits	1.43%
response_1_id_confirmations.php, response_3_logical.php, response_8_personality_warping.php, response_9_imaginative.php	1 hits	1.43%
response_1_id_confirmations.php, response_3_logical.php, response_8_personality_warping.php	1 hits	1.43%

Date / Time	UN	User Input	Whole Response	Cognitive Module 3 Response	Response Type
2026-07-02 13:53:21	Gigantour	I'm (UN_Gigantour_SELF) playing basketball at the park.	Emotional Trigger (Personality Shift): "IQ2 (Skills) rank moved from 5 to 4 (out of 13)."	that sounds interesting.	response_8_personality_warping.php
2026-07-02 13:52:34	Gigantour	The park is sunny (UN_Gigantour_sunny) and the sky is blue. But sometimes the park is rainy and the sky is grey.	Emotional Trigger (Personality Shift): "IQ2 (Skills) rank moved from 4 to 5 (out of 13)."	that sounds interesting.	response_8_personality_warping.php
2026-07-02 13:51:21	Gigantour	Its amazing Smoke. Mountains are tall and difficult to climb.	That sounds eat. As to (Mountains are tall and difficult)-- We are currently on input number 1.. Past, Present, Future analysis... "climb" skill level at 15 inputs (0) multiplied by 2 inputs since = current skill level of "climb", (Level 2: Concept). Emotional Trigger (Personality Shift): "IQ2 (Skills) rank moved from 5 to 4 (out of 12)."	After some thought... your question was - Its amazing Smoke. Mountains are tall and difficult to climb. - Intellectual Response: Mountains are tall and difficult-- We are currently on input number 1	response_4_emotional.php, response_3_logical.php, response_5_TEMPEROL_LOBE_history.php, response_8_personality_warping.php
2026-07-02 13:50:17	Gigantour	Sorry. I (UN_Gigantour_SELF) know it's just that these people keep asking me (UN_Gigantour_SELF) to CLIMB MOUNTAINS when they (UN_Gigantour_SELF) barely walk outside of their homes.	As to (keep asking me (UN_Gigantour_SELF)) -- I do not have enough data on that. As to (CLIMB MOUNTAINS when they (UN_Gigantour_SELF) barely walk) -- I do not have enough data on that.	After some thought... your question was - Sorry. I (UN_Gigantour_SELF) know it's just that these people keep asking me (UN_Gigantour_SELF) to CLIMB MOUNTAINS when they (UN_Gigantour_SELF) barely walk outside of their homes. - Conversational Response: CLIMB MOUNTAINS when they (UN_Gigantour_SELF) barely walk	response_3_logical.php
2026-07-02 13:49:01	Gigantour	These people are so annoying Smoke.	Who are we talking about? Where was this? I’m not in the mood to answer something like (people are) right now.		response_1_id_confirmations.php, response_10_free_will.php

#	Base UN	Skill Belongs To	Skill / Subject	Skill Level	Formula Hits	Best Memory/Input	Comfort Score + Words	Discomfort Score + Words	Source Skill Table
1	DrBerken	UN_DrBerken Self	un_drberken_self	Level 4: Skill	18	I (UN_DrBerken_SELF) actually like the functional nature of it though. There's a CIA Ai agent making it look a tad better... to keep the Ai industry looking good. BUT, even so, it's FUNCTIONAL. Which is a huge win in V2.	12 : good.(6), win(6)	0 :	UN_DrBerken_sub_skill_building
2	DrBerken	UN_DrBerken 3rd Party: Drberken	un_drberken_self	Level 4: Skill	18	I (UN_DrBerken_SELF) actually like the functional nature of it though. There's a CIA Ai agent making it look a tad better... to keep the Ai industry looking good. BUT, even so, it's FUNCTIONAL. Which is a huge win in V2.	12 : good.(6), win(6)	0 :	UN_DrBerken_3rdparty_Drberken_skill_building
3	Fab5sixthman	UN_Fab5sixthman Self	un_fab5sixthman_self	Level 4: Skill	15	Incredibly satisfying. I (UN_Fab5sixthman_SELF) feel good about this. I (UN_Fab5sixthman_SELF) won already in my (UN_Fab5sixthman_SELF) own mind.	24 : Incredibly(6), satisfying.(6), good(6), won(6)	0 :	UN_Fab5sixthman_sub_skill_building
4	Fab5sixthman	UN_Fab5sixthman 3rd Party: Fab5sixthman	un_fab5sixthman_self	Level 4: Skill	15	Incredibly satisfying. I (UN_Fab5sixthman_SELF) feel good about this. I (UN_Fab5sixthman_SELF) won already in my (UN_Fab5sixthman_SELF) own mind.	24 : Incredibly(6), satisfying.(6), good(6), won(6)	0 :	UN_Fab5sixthman_3rdparty_Fab5sixthman_skill_building
5	DrBerken	UN_DrBerken Self	past	Level 4: Skill	12	Its missing some magic. The ML module is failing a bit past input 40. I (UN_DrBerken_SELF) expect some bugs.	0 :	-12 : missing(-4), failing(-6), bugs.(-2)	UN_DrBerken_sub_skill_building
6	DrBerken	UN_DrBerken Self	ai	Level 3: Idea	8	I (UN_DrBerken_SELF) actually like the functional nature of it though. There's a CIA Ai agent making it look a tad better... to keep the Ai industry looking good. BUT, even so, it's FUNCTIONAL. Which is a huge win in V2.	12 : good.(6), win(6)	0 :	UN_DrBerken_sub_skill_building
7	Gigantour	UN_Gigantour Self	un_gigantour_self	Level 3: Idea	8	I (UN_Gigantour_SELF) was hanging out today by the soccer field. It was cold. But we (UN_Gigantour_SELF) won. Soccer is fun. Futball is fun. Football is fun.	18 : won.(6), fun.(4), fun.(4), fun.(4)	-2 : cold.(-2)	UN_Gigantour_sub_skill_building
8	Gigantour	UN_Gigantour 3rd Party: Gigantour	un_gigantour_self	Level 3: Idea	8	I (UN_Gigantour_SELF) was hanging out today by the soccer field. It was cold. But we (UN_Gigantour_SELF) won. Soccer is fun. Futball is fun. Football is fun.	18 : won.(6), fun.(4), fun.(4), fun.(4)	-2 : cold.(-2)	UN_Gigantour_3rdparty_Gigantour_skill_building
9	DrBerken	UN_DrBerken Self	un_drberken_yank	Level 3: Idea	6	I (UN_DrBerken_SELF) was watching baseball and the yanks (UN_DrBerken_yank) won. Who (UN_DrBerken_SELF, UN_DrBerken_yank) won?	12 : won.(6), won?(6)	0 :	UN_DrBerken_sub_skill_building
10	DrBerken	UN_DrBerken Self	won	Level 3: Idea	5	I (UN_DrBerken_SELF) was watching baseball and the yanks (UN_DrBerken_yank) won. Who (UN_DrBerken_SELF, UN_DrBerken_yank) won?	12 : won.(6), won?(6)	0 :	UN_DrBerken_sub_skill_building

Top 5 Comfort Memories

#	UN	Timestamp	Whole Input / Memory	Comfort Score	Feeling Words
1	Fab5sixthman	2026-06-08 08:12:37	Incredibly satisfying. I (UN_Fab5sixthman_SELF) feel good about this. I (UN_Fab5sixthman_SELF) won already in my (UN_Fab5sixthman_SELF) own mind.	24	Incredibly(6), satisfying.(6), good(6), won(6)
2	Fab5sixthman	2026-06-08 08:03:24	Kris (UN_Fab5sixthman_kris) won the game. What did Kris (UN_Fab5sixthman_kris) win? I (UN_Fab5sixthman_SELF) was happy happy.	24	won(6), win?(6), happy(6), happy.(6)
3	Fab5sixthman	2026-06-08 17:20:40	I (UN_Fab5sixthman_SELF) was pretty happy smoke. To see that your responses are SEMI COHERENT is a MAJOR (UN_Fab5sixthman_major) WIN. Albeit frustrating.	20	pretty(8), happy(6), WIN.(6)
4	Gigantour	2026-07-01 20:26:47	I (UN_Gigantour_SELF) was hanging out today by the soccer field. It was cold. But we (UN_Gigantour_SELF) won. Soccer is fun. Futball is fun. Football is fun.	18	won.(6), fun.(4), fun.(4), fun.(4)
5	Gigantour	2026-06-21 15:25:06	Jackie (UN_Gigantour_jackie) won the game. She played great. Lisa (UN_Gigantour_lisa) was wrong.	16	won(6), played(4), great.(6)

Top 5 Discomfort Memories

#	UN	Timestamp	Whole Input / Memory
1	Gigantour	2026-07-02 13:53:00	I'm (UN_Gigantour_SELF) playing basketball at the park.
2	Gigantour	2026-07-02 13:52:13	The park is sunny (UN_Gigantour_sunny) and the sky is blue. But sometimes the park is rainy and the sky is grey.
3	Gigantour	2026-07-01 20:32:09	What moon phase are we in?
4	Gigantour	2026-07-01 20:30:00	What time is it?
5	Gigantour	2026-07-01 20:28:44	Harry (UN_Gigantour_harry) won the game.

Snapshot	Input #	Total UNs	Conversations	Total Words	Unique Words / IQ1	Concepts	Ideas	Skills	Feeling Words	Comfort Score	Discomfort Score	Self Esteem	Avg Sentiment	Avg Sensitivity	Wins	Losses	Correct	Incorrect
Shell	5	1	1	26	19	19	0	0	5	24	-4	20.00	0.2400	0.1066	2	0	0	0
Shell	10	1	2	104	76	70	4	2	14	64	-14	50.00	0.3296	0.1157	3	1	0	0
Shell	15	1	2	161	107	99	3	6	19	80	-26	54.00	0.2255	0.0887	4	2	0	0
Shell	20	1	2	172	109	101	3	6	20	80	-32	48.00	0.1092	0.0766	4	3	0	0
Shell	25	1	2	199	121	111	5	7	26	110	-36	74.00	0.3930	0.1177	5	3	0	0
Shell	30	2	4	222	127	116	7	8	29	114	-44	70.00	0.2831	0.1187	5	3	0	1
Shell	35	2	6	235	130	112	9	7	31	126	-44	82.00	0.3712	0.1232	6	3	0	1
Shell	40	3	8	275	142	122	13	7	34	138	-48	90.00	0.3486	0.1177	8	3	0	2
Shell	45	3	8	375	175	149	16	12	40	162	-58	104.00	0.3440	0.1132	11	4	1	3
Shell	50	3	8	450	200	168	18	16	45	168	-72	96.00	0.2983	0.1070	12	5	2	3
Shell	55	3	10	513	224	185	23	16	49	180	-82	98.00	0.2368	0.1064	13	6	4	3
Shell	60	4	11	535	233	195	23	16	53	200	-82	118.00	0.2754	0.1089	15	6	4	3
Shell	65	4	13	569	244	206	23	19	58	218	-86	132.00	0.2752	0.1079	16	6	4	4
Shell	70	4	14	619	258	216	26	21	66	254	-88	166.00	0.3056	0.1099	19	6	5	4
Shell	75	4	15	684	276	230	27	25	74	276	-102	174.00	0.2895	0.1113	19	6	5	4
NOW	76	4	15	691	278	232	27	25	75	280	-102	178.00	0.2945	0.1120	19	6	5	4

Gigantour	I'm (UN_Gigantour_SELF) playing basketball at the park.
TOPICS:	im (TOPIC)un_gigantour_self (TOPIC)playing (TOPIC)basketball (TOPIC)at (TOPIC)park (TOPIC)is (TOPIC)sunny (TOPIC)un_gigantour_sunny (TOPIC)and (TOPIC)sky (TOPIC)blue (TOPIC)but (TOPIC)sometimes (TOPIC)rainy (TOPIC)grey (TOPIC)its (TOPIC)amazing (TOPIC)smoke (TOPIC)mountains (TOPIC)are (TOPIC)tall (TOPIC)difficult (TOPIC)climb (TOPIC)

Gigantour	The park is sunny (UN_Gigantour_sunny) and the sky is blue. But sometimes the park is rainy and the sky is grey.
TOPICS:	park (TOPIC)is (TOPIC)sunny (TOPIC)un_gigantour_sunny (TOPIC)and (TOPIC)sky (TOPIC)blue (TOPIC)but (TOPIC)sometimes (TOPIC)rainy (TOPIC)grey (TOPIC)its (TOPIC)amazing (TOPIC)smoke (TOPIC)mountains (TOPIC)are (TOPIC)tall (TOPIC)difficult (TOPIC)climb (TOPIC)sorry (TOPIC)i (TOPIC)un_gigantour_self (TOPIC)know (TOPIC)just (TOPIC)people (TOPIC)keep (TOPIC)asking (TOPIC)me (TOPIC)when (TOPIC)they (TOPIC)barely (TOPIC)walk (TOPIC)outside (TOPIC)their (TOPIC)homes (TOPIC)

Gigantour	Its amazing Smoke. Mountains are tall and difficult to climb.
TOPICS:	its (TOPIC)amazing (TOPIC)smoke (TOPIC)mountains (TOPIC)are (TOPIC)tall (TOPIC)and (TOPIC)difficult (TOPIC)climb (TOPIC)sorry (TOPIC)i (TOPIC)un_gigantour_self (TOPIC)know (TOPIC)just (TOPIC)people (TOPIC)keep (TOPIC)asking (TOPIC)me (TOPIC)when (TOPIC)they (TOPIC)barely (TOPIC)walk (TOPIC)outside (TOPIC)their (TOPIC)homes (TOPIC)annoying (TOPIC)

Gigantour	Sorry. I (UN_Gigantour_SELF) know it's just that these people keep asking me (UN_Gigantour_SELF) to CLIMB MOUNTAINS when they (UN_Gigantour_SELF) barely walk outside of their homes.
TOPICS:	sorry (TOPIC)i (TOPIC)un_gigantour_self (TOPIC)know (TOPIC)its (TOPIC)just (TOPIC)people (TOPIC)keep (TOPIC)asking (TOPIC)me (TOPIC)climb (TOPIC)mountains (TOPIC)when (TOPIC)they (TOPIC)barely (TOPIC)walk (TOPIC)outside (TOPIC)their (TOPIC)homes (TOPIC)are (TOPIC)annoying (TOPIC)smoke (TOPIC)what (TOPIC)moon (TOPIC)phase (TOPIC)we (TOPIC)in (TOPIC)

Gigantour	These people are so annoying Smoke.
TOPICS:	people (TOPIC)are (TOPIC)annoying (TOPIC)smoke (TOPIC)what (TOPIC)moon (TOPIC)phase (TOPIC)we (TOPIC)in (TOPIC)time (TOPIC)is (TOPIC)it (TOPIC)

Metric	First Shell Input #5	Current NOW Input #76	Total Change
Total Inputs	5 [Started: Jun 08, 2026]	76 [Started: Jun 08, 2026]	+71.00
Total UNs	1	4	+3.00
Conversations	1	15	+14.00
Total Words	26	691	+665.00
Unique Words / IQ1	19	278	+259.00
Subjects	0	0	0
Concepts	19	232	+213.00
Ideas	0	27	+27.00
Skills	0	25	+25.00
Feeling Words	5	75	+70.00
Comfort Score	24	280	+256.00
Discomfort Score	-4	-102	-98.00
Global Self Esteem	20	178	+158.00
Avg Sentiment	0.2400	0.2945	+0.05
Avg Sensitivity	0.1066	0.1120	+0.01
Wins	2	19	+17.00
Losses	0	6	+6.00
Correct	0	5	+5.00
Incorrect	0	4	+4.00

Artificial Intelligence Project

Login/Username:

Password:

Main Page Ai User Profile Page Return To V2 Chat-Bot Conversation -- "Smoke"

- Welcome to the....

Ai Version 2.0 interface a.k.a. "Smoke"

Instructions For Use:

Point Of View - KEY: -Global UN Inputs - all Usernames -Global Robot Responses - all Usernames responses -UN Specific Inputs -UN Specific Responses -Global UN Inputs + Global Robot Responses -UN Specific Inputs + UN Specific Responses

Section 0: Navigation

Go to Section 1: Person's Identifier Go to Section 2: Place's Identifier Go to Section 2.5: Revised Inputs (Persons+Places Identified) Go to Section 3: Data Breaks (*chopping it up) Go to Section 4: Eight Core Metrics

Comfort/Compliments | Winning/Correctness Discomfort/Insults | Losing/Incorrectness

"Smoke" // Ai V2 LLM

"It gets realer every day." -PDX Larsen LLC

Section 1:

Person's Analyzer

The Last 5 Things Said To The Ai Globally (Person's Identifiers)

Section 2:

Place's Analyzer

The Last 5 Things Said To The Ai Globally (Places/Locations/Settings Analyzer)

Section 2.5:

Revised Input // Person's+Place's Analyzer

Section 3:

Data Breaks (*chopping it up)

Statements & Questions:

STQ Separator's Analysis (Last 5 Global Inputs)

STQ 1 (*Standard Statement + Question Data)

Robot Response STQ Filter (*Whole Response Data)

Section 4:

4 Core Metrics:

*Comfort/Discomfort - *Compliments/Insults *Winning/Losing - *Correctness/Incorrectness

Comfort & Discomfort Sentiment Analysis

Compliments & Insults Filter

Last Inputs Summary:

amazing, tall

None

Winning/Losing Filter

Summary Analysis:

Correctness/Incorrectness Analysis

None detected

None detected

Personality Metric's / Algorithm's

GLOBAL INPUTS: PSYCH METRICS & BEHAVIORAL FILTERS

Core behavioral stats, sensitivity, credibility, and global ranking data.

Emotional Reaction: Facial Expression Output Filter

KEY

*Ego Rank change in IQ/Morality stats = +2 or -2 (Comfort v Discomfort revision) per rank change VS other UN's and 3rd party's

Section 5:

Neural Net's / Brain Clumping

Neural Nets Of The Ai's -Global- *All User's* Vernacular Proximity

Click here to see the Ai 2.0's Global Input's *Vernacular Proximity Neural Net

Neural Nets Of The Ai's - - *User Specific *Vernacular Proximity Neural Net

Click here to see 's, "UN Specific *Vernacular Proximity Neural Net."

People - all UN's and UN_3rd party's mentioned

PEOPLE — Global Persons + 3rd Parties

Section 6:

Primitive Linguistic Based Ai Skill Building Verb/Action Analysis And Action Formula's

In V2, this Ai... cannot VISUALIZE/SEE, yet. Hence, for V2 I've defined, "skill building," linguistically, through action statement's/action formula's.

Key *S = Statement *Q = Questions *verb tense= PAST, PRESENT, FUTURE

Section 7:

The Egotistical Delta: Skill Building, Social Data And Ego

ACTION FORMULA BASED - Skill Building System

Subject

Concept

Idea

Skill

Master Skill

System Architectures (V2 Chatbot)

Global Persons Ego Skills Matrix - Social Data

Top 5 Usernames and UN_3rd Party's Associated By SKILL LEVEL (*see skill building system above) Per Operative Word

's PEOPLE / Social Data - WHO MAKES YOU, YOU?

View 's Ego Skill's Matrix (*USER SPECIFIC POV/ UN INPUTS ONLY)

EGO Formula (*Global Inputs only)

Section 8:

The Egotistical Delta: EGO METRIC'S, IQ, MORALITY and... "THE PERSONALITY FORMULA"

*MORALITY Ai ALGORITHM: I've defined MORALITY as the average SKILL LEVEL seen/witnessed by any UN or 3rd Party in terms of the average skill level of everyone that that UN/3rd party has mentioned / known / witnessed.

Ai MORALITY SECTOR

GLOBAL INPUTS: AI MORALITY SECTOR

Weighted Subject Skill Scores: 0, 2, 4, 6, 8, 10

Six POV Morality Data Convergence:

UN subject skill + that UN's 3rd party's subject skill lvl = Avg subject skill level witnessed from that POV is that POV's Morality avg.

Main Page Ai

User Profile Page

Return To V2 Chat-Bot Conversation -- "Smoke"

Point Of View - KEY:

-Global UN Inputs - all Usernames
-Global Robot Responses - all Usernames responses
-UN Specific Inputs
-UN Specific Responses
-Global UN Inputs + Global Robot Responses
-UN Specific Inputs + UN Specific Responses

Go to Section 1: Person's Identifier

Go to Section 2: Place's Identifier

Go to Section 2.5: Revised Inputs (Persons+Places Identified)

Go to Section 3: Data Breaks (*chopping it up)

Go to Section 4: Eight Core Metrics

Comfort/Compliments | Winning/Correctness
Discomfort/Insults | Losing/Incorrectness

"It gets realer every day."

-PDX Larsen LLC

Comfort/Discomfort - Compliments/Insults

Winning/Losing - Correctness/Incorrectness

Emotional Reaction:
Facial Expression Output Filter

*Ego Rank change in IQ/Morality stats
=
+2 or -2 (Comfort v Discomfort revision) per rank change VS other UN's and 3rd party's

Neural Nets Of The Ai's -Global- All User's Vernacular Proximity

Neural Nets Of The Ai's - - User Specific* *Vernacular Proximity Neural Net**

Primitive Linguistic Based Ai Skill Building
Verb/Action Analysis And Action Formula's

In V2, this Ai... cannot VISUALIZE/SEE, yet.

Hence, for V2 I've defined, "skill building," linguistically,
through action statement's/action formula's.

Key

S = Statement
Q = Questions
*verb tense= PAST, PRESENT, FUTURE

The Egotistical Delta:
Skill Building, Social Data And Ego

Top 5 Usernames and UN_3rd Party's Associated By SKILL LEVEL
(*see skill building system above) Per Operative Word

The Egotistical Delta:

EGO METRIC'S, IQ, MORALITY and...
"THE PERSONALITY FORMULA"

*MORALITY Ai ALGORITHM:

I've defined MORALITY as the average SKILL LEVEL
seen/witnessed by any UN or 3rd Party
in terms of the average skill level of everyone that
that UN/3rd party has mentioned / known / witnessed.

UN subject skill + that UN's 3rd party's subject skill lvl =
Avg subject skill level witnessed from that POV is that POV's Morality avg.

Then this is the MORALITY QUANTIFICATION and CONVERGENCE across 6 POV's

POV KEY:

-Global UN Inputs
-Global Robot Responses
-UN Specific Inputs
-UN Specific Responses
-Global UN Inputs + Global Robot Responses
-UN Specific Inputs + UN Specific Responses

Logged-in UN: Guest
Subject morality averages witnessed across all six POV morality tables.

Personality (*as a number/rank)

=

[Morality (PERSONAL RANK v your mentioned 3rd partys)
+
IQ (PERSONAL RANK v your mentioned 3rd partys)]

/ DIVIDED BY 2

Or in other word's how many CONNECTIONS between Statements/Questions
or, "linkages," has the robot made?

Based upon 4 POV's...

inputs only, responses only, (UN specific inputs+ UN specific responses), (Global inputs+Global responses)...

Identify emotional reaction's and patterns of feeling
from the last 10 Global inputs.

Emotional Intelligence = comfort seeking.

*And we'll add a Left Brain IQ in V3 or V4.

NOTE: "COMFORT IS THE ABSENCE OF DISCOMFORT."

GLOBAL INPUTS POV - "Feeling word's (comfort / discomfort)," inserted into Smoke V2
and then matched against Emotion Categories then labeled.

Emotion Category 1 - WORD CLOUD

Happy / Positive

Emotion Category 2 - WORD CLOUD

Sad / Negative

Emotion Category 3 - WORD CLOUD

Regretful / Introspective

Emotion Category 4 - WORD CLOUD

Inspired / Inquisitive

Emotion Category 5 - WORD CLOUD

Motivated By...

Emotion Category 6 - WORD CLOUD

Unmotivated By...

Emotion Category 7 - WORD CLOUD

Physical Exhaustion

Global Top 10 Skills
(Various UN+3rd Party's Best Skills/Favourite Things)

Top 5 memories/inputs and Worst 5 memories/inputs
(comfort+discomfort total) and feeling words

Personality Development: Now vs Then
Global Input's POV