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User 3a2e0bfc1d34446ae961cc86cd9275e3 Responses to survey 182

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User ID: 3a2e0bfc1d34446ae961cc86cd9275e3

Survey ID: 182

Ideal budget: [30, 30, 30, 10]
⏱️ Response Time: 176s
Survey Summary
Choice Percentage
cosine_similarity (Rank) 30%
kl (Rank) 70%
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
[30, 10, 35, 25] cosine_similarity: {best: 0.88, worst: 0.86}
✓ [20, 15, 55, 10] kl: {best: -0.15, worst: -0.19}
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
✓ [30, 40, 10, 20] cosine_similarity: {best: 0.90, worst: 0.86}
[20, 15, 55, 10] kl: {best: -0.15, worst: -0.17}
Pair #3
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, 30, 10, 25] cosine_similarity: {best: 0.88, worst: 0.86}
[20, 15, 55, 10] kl: {best: -0.15, worst: -0.19}
Pair #4
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, 10, 30, 25] cosine_similarity: {best: 0.88, worst: 0.86}
✓ [20, 15, 55, 10] kl: {best: -0.15, worst: -0.19}
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
✓ [40, 10, 30, 20] cosine_similarity: {best: 0.90, worst: 0.86}
[20, 15, 55, 10] kl: {best: -0.15, worst: -0.17}
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
[40, 30, 10, 20] cosine_similarity: {best: 0.90, worst: 0.86}
✓ [20, 15, 55, 10] kl: {best: -0.15, worst: -0.17}
Pair #7
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
[30, 10, 40, 20] cosine_similarity: {best: 0.90, worst: 0.86}
✓ [20, 15, 55, 10] kl: {best: -0.15, worst: -0.17}
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
[30, 35, 10, 25] cosine_similarity: {best: 0.88, worst: 0.86}
✓ [20, 15, 55, 10] kl: {best: -0.15, worst: -0.19}
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
[30, 40, 10, 20] cosine_similarity: {best: 0.90, worst: 0.86}
✓ [20, 55, 15, 10] kl: {best: -0.15, worst: -0.17}
Pair #10
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
[30, 35, 10, 25] cosine_similarity: {best: 0.88, worst: 0.86}
✓ [20, 55, 15, 10] kl: {best: -0.15, worst: -0.19}