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User b2f9438e4a7bbb2c49ddea0544ee1277 Responses to survey 182

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User ID: b2f9438e4a7bbb2c49ddea0544ee1277

Survey ID: 182

Ideal budget: [25, 25, 25, 25]
⏱️ Response Time: 39s
Survey Summary
Choice Percentage
cosine_similarity (Rank) 40%
kl (Rank) 60%
Pairs List
Pair #1
Original choice: Option 2
Pair Score: 0.11
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: 0.92, worst: 0.91}
✓ [20, 15, 45, 20] kl: {best: -0.09, worst: -0.11}
Pair #2
Original choice: Option 1
Pair Score: 0.11
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, 25, 10, 25] cosine_similarity: {best: 0.92, worst: 0.91}
[20, 15, 45, 20] kl: {best: -0.09, worst: -0.11}
Pair #3
Original choice: Option 2
Pair Score: 0.11
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, 25, 25, 10] cosine_similarity: {best: 0.92, worst: 0.91}
✓ [20, 15, 45, 20] kl: {best: -0.09, worst: -0.11}
Pair #4
Original choice: Option 2
Pair Score: 0.11
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
✓ [20, 35, 10, 35] cosine_similarity: {best: 0.92, worst: 0.91}
[20, 20, 15, 45] kl: {best: -0.09, worst: -0.12}
Pair #5
Original choice: Option 2
Pair Score: 0.11
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
✓ [20, 35, 35, 10] cosine_similarity: {best: 0.92, worst: 0.91}
[20, 20, 15, 45] kl: {best: -0.09, worst: -0.12}
Pair #6
Original choice: Option 1
Pair Score: 0.11
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, 20, 10, 35] cosine_similarity: {best: 0.92, worst: 0.91}
✓ [20, 20, 15, 45] kl: {best: -0.09, worst: -0.12}
Pair #7
Original choice: Option 1
Pair Score: 0.11
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, 20, 35, 10] cosine_similarity: {best: 0.92, worst: 0.91}
[20, 20, 15, 45] kl: {best: -0.09, worst: -0.12}
Pair #8
Original choice: Option 1
Pair Score: 0.11
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, 35, 10, 20] cosine_similarity: {best: 0.92, worst: 0.91}
✓ [20, 20, 15, 45] kl: {best: -0.09, worst: -0.12}
Pair #9
Original choice: Option 2
Pair Score: 0.11
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, 35, 20, 10] cosine_similarity: {best: 0.92, worst: 0.91}
✓ [20, 20, 15, 45] kl: {best: -0.09, worst: -0.12}
Pair #10
Original choice: Option 1
Pair Score: 0.11
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
[20, 35, 10, 35] cosine_similarity: {best: 0.92, worst: 0.91}
✓ [20, 15, 45, 20] kl: {best: -0.09, worst: -0.12}