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User 57d5a13d9dd8722e576e8e97aefcbd41 Responses to survey 182

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User ID: 57d5a13d9dd8722e576e8e97aefcbd41

Survey ID: 182

Ideal budget: [40, 20, 20, 20]
⏱️ Response Time: 102s
Survey Summary
Choice Percentage
cosine_similarity (Rank) 20%
kl (Rank) 80%
Pairs List
Pair #1
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
✓ [70, 10, 10, 10] cosine_similarity: {best: 0.89, worst: 0.85}
[25, 15, 15, 45] kl: {best: -0.14, worst: -0.19}
Pair #2
Original choice: Option 2
Pair Score: 0.10
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
[70, 10, 10, 10] cosine_similarity: {best: 0.89, worst: 0.85}
✓ [25, 15, 45, 15] kl: {best: -0.14, worst: -0.19}
Pair #3
Original choice: Option 2
Pair Score: 0.10
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
[70, 10, 10, 10] cosine_similarity: {best: 0.89, worst: 0.85}
✓ [25, 45, 15, 15] kl: {best: -0.14, worst: -0.19}
Pair #4
Original choice: Option 1
Pair Score: 0.10
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
[70, 10, 10, 10] cosine_similarity: {best: 0.89, worst: 0.86}
✓ [20, 20, 20, 40] kl: {best: -0.14, worst: -0.19}
Pair #5
Original choice: Option 1
Pair Score: 0.10
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
[70, 10, 10, 10] cosine_similarity: {best: 0.89, worst: 0.86}
✓ [20, 20, 40, 20] kl: {best: -0.14, worst: -0.19}
Pair #6
Original choice: Option 1
Pair Score: 0.10
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
[70, 10, 10, 10] cosine_similarity: {best: 0.89, worst: 0.86}
✓ [20, 40, 20, 20] kl: {best: -0.14, worst: -0.19}
Pair #7
Original choice: Option 2
Pair Score: 0.09
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
[50, 10, 10, 30] cosine_similarity: {best: 0.94, worst: 0.92}
✓ [25, 35, 20, 20] kl: {best: -0.08, worst: -0.11}
Pair #8
Original choice: Option 2
Pair Score: 0.09
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
✓ [50, 10, 30, 10] cosine_similarity: {best: 0.94, worst: 0.92}
[25, 20, 35, 20] kl: {best: -0.08, worst: -0.11}
Pair #9
Original choice: Option 2
Pair Score: 0.09
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
[50, 10, 10, 30] cosine_similarity: {best: 0.94, worst: 0.92}
✓ [25, 20, 35, 20] kl: {best: -0.08, worst: -0.11}
Pair #10
Original choice: Option 2
Pair Score: 0.09
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
[50, 10, 30, 10] cosine_similarity: {best: 0.94, worst: 0.92}
✓ [25, 20, 20, 35] kl: {best: -0.08, worst: -0.11}