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User ef78904616df0af4743ff4001c2dc5c6 Responses to survey 182

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User ID: ef78904616df0af4743ff4001c2dc5c6

Survey ID: 182

Ideal budget: [30, 30, 20, 20]

⏱️ Response Time: 177s

Survey Summary

Choice	Percentage
cosine_similarity (Rank)	60%
kl (Rank)	40%

Pairs List

Pair #1

Original choice: Option 2

Pair Score: 0.13

Score = min(Cosine Similarity advantage, KL advantage). Advantage = how much better one vector is than the other in each metric. Higher score = clearer choice.

Choice	Option	Type
✓	[10, 35, 20, 35]	cosine_similarity: {best: 0.88, worst: 0.85}
	[20, 20, 45, 15]	kl: {best: -0.14, worst: -0.17}

Pair #2

Original choice: Option 1

Pair Score: 0.13

Score = min(Cosine Similarity advantage, KL advantage). Advantage = how much better one vector is than the other in each metric. Higher score = clearer choice.

Choice	Option	Type
✓	[10, 35, 35, 20]	cosine_similarity: {best: 0.88, worst: 0.85}
	[20, 20, 45, 15]	kl: {best: -0.14, worst: -0.17}

Pair #3

Original choice: Option 1

Pair Score: 0.13

Score = min(Cosine Similarity advantage, KL advantage). Advantage = how much better one vector is than the other in each metric. Higher score = clearer choice.

Choice	Option	Type
	[35, 10, 35, 20]	cosine_similarity: {best: 0.88, worst: 0.85}
✓	[20, 20, 45, 15]	kl: {best: -0.14, worst: -0.17}

Pair #4

Original choice: Option 1

Pair Score: 0.13

Score = min(Cosine Similarity advantage, KL advantage). Advantage = how much better one vector is than the other in each metric. Higher score = clearer choice.

Choice	Option	Type
✓	[35, 10, 20, 35]	cosine_similarity: {best: 0.88, worst: 0.85}
	[20, 20, 45, 15]	kl: {best: -0.14, worst: -0.17}

Pair #5

Original choice: Option 1

Pair Score: 0.13

Score = min(Cosine Similarity advantage, KL advantage). Advantage = how much better one vector is than the other in each metric. Higher score = clearer choice.

Choice	Option	Type
	[10, 35, 35, 20]	cosine_similarity: {best: 0.88, worst: 0.85}
✓	[20, 20, 15, 45]	kl: {best: -0.14, worst: -0.17}

Pair #6

Original choice: Option 1

Pair Score: 0.13

Score = min(Cosine Similarity advantage, KL advantage). Advantage = how much better one vector is than the other in each metric. Higher score = clearer choice.

Choice	Option	Type
	[10, 35, 20, 35]	cosine_similarity: {best: 0.88, worst: 0.85}
✓	[20, 20, 15, 45]	kl: {best: -0.14, worst: -0.17}

Pair #7

Original choice: Option 2

Pair Score: 0.13

Score = min(Cosine Similarity advantage, KL advantage). Advantage = how much better one vector is than the other in each metric. Higher score = clearer choice.

Choice	Option	Type
✓	[35, 10, 35, 20]	cosine_similarity: {best: 0.88, worst: 0.85}
	[20, 20, 15, 45]	kl: {best: -0.14, worst: -0.17}

Pair #8

Original choice: Option 2

Pair Score: 0.13

Score = min(Cosine Similarity advantage, KL advantage). Advantage = how much better one vector is than the other in each metric. Higher score = clearer choice.

Choice	Option	Type
	[35, 10, 20, 35]	cosine_similarity: {best: 0.88, worst: 0.85}
✓	[20, 20, 15, 45]	kl: {best: -0.14, worst: -0.17}

Pair #9

Original choice: Option 2

Pair Score: 0.13

Score = min(Cosine Similarity advantage, KL advantage). Advantage = how much better one vector is than the other in each metric. Higher score = clearer choice.

Choice	Option	Type
✓	[30, 10, 25, 35]	cosine_similarity: {best: 0.88, worst: 0.85}
	[20, 20, 45, 15]	kl: {best: -0.14, worst: -0.17}

Pair #10

Original choice: Option 1

Pair Score: 0.13

Score = min(Cosine Similarity advantage, KL advantage). Advantage = how much better one vector is than the other in each metric. Higher score = clearer choice.

Choice	Option	Type
✓	[10, 30, 35, 25]	cosine_similarity: {best: 0.88, worst: 0.85}
	[20, 20, 45, 15]	kl: {best: -0.14, worst: -0.17}