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User 9cadb05af4f752ce6adb509b92e6de0c Responses to survey 182

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User ID: 9cadb05af4f752ce6adb509b92e6de0c

Survey ID: 182

Ideal budget: [30, 30, 25, 15]

⏱️ Response Time: 100s

Survey Summary

Choice	Percentage
cosine_similarity (Rank)	10%
kl (Rank)	90%

Pairs List

Pair #1

Original choice: Option 1

Pair Score: 0.14

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, 35, 25]	cosine_similarity: {best: 0.89, worst: 0.87}
✓	[20, 20, 50, 10]	kl: {best: -0.13, worst: -0.17}

Pair #2

Original choice: Option 1

Pair Score: 0.14

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: 0.89, worst: 0.87}
✓	[20, 20, 50, 10]	kl: {best: -0.13, worst: -0.17}

Pair #3

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
	[40, 10, 25, 25]	cosine_similarity: {best: 0.89, worst: 0.87}
✓	[20, 20, 50, 10]	kl: {best: -0.13, worst: -0.17}

Pair #4

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, 40, 25, 25]	cosine_similarity: {best: 0.89, worst: 0.87}
✓	[20, 20, 50, 10]	kl: {best: -0.13, worst: -0.17}

Pair #5

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
	[40, 10, 40, 10]	cosine_similarity: {best: 0.88, worst: 0.84}
✓	[20, 20, 20, 40]	kl: {best: -0.15, worst: -0.19}

Pair #6

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, 40, 40, 10]	cosine_similarity: {best: 0.88, worst: 0.84}
✓	[20, 20, 20, 40]	kl: {best: -0.15, worst: -0.19}

Pair #7

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
	[45, 10, 35, 10]	cosine_similarity: {best: 0.88, worst: 0.86}
✓	[25, 15, 50, 10]	kl: {best: -0.15, worst: -0.18}

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
✓	[45, 10, 35, 10]	cosine_similarity: {best: 0.88, worst: 0.86}
	[15, 25, 50, 10]	kl: {best: -0.15, worst: -0.18}

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
	[10, 45, 35, 10]	cosine_similarity: {best: 0.88, worst: 0.86}
✓	[15, 25, 50, 10]	kl: {best: -0.15, worst: -0.18}

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, 45, 35, 10]	cosine_similarity: {best: 0.88, worst: 0.86}
✓	[25, 15, 50, 10]	kl: {best: -0.15, worst: -0.18}