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User 7b94544fb858083bd7c379bd53cadb17 Responses to survey 182

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User ID: 7b94544fb858083bd7c379bd53cadb17

Survey ID: 182

Ideal budget: [50, 20, 20, 10]
⏱️ Response Time: 103s
Survey Summary
Choice Percentage
cosine_similarity (Rank) 0%
kl (Rank) 100%
Pairs List
Pair #1
Original choice: Option 1
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
[10, 30, 35, 25] cosine_similarity: {best: 0.66, worst: 0.62}
✓ [20, 15, 15, 50] kl: {best: -0.41, worst: -0.52}
Pair #2
Original choice: Option 1
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
[10, 35, 30, 25] cosine_similarity: {best: 0.66, worst: 0.62}
✓ [20, 15, 15, 50] kl: {best: -0.41, worst: -0.52}
Pair #3
Original choice: Option 1
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
[10, 40, 20, 30] cosine_similarity: {best: 0.63, worst: 0.57}
✓ [20, 15, 10, 55] kl: {best: -0.48, worst: -0.56}
Pair #4
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
[10, 40, 20, 30] cosine_similarity: {best: 0.63, worst: 0.57}
✓ [20, 10, 15, 55] kl: {best: -0.48, worst: -0.56}
Pair #5
Original choice: Option 1
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
[10, 20, 40, 30] cosine_similarity: {best: 0.63, worst: 0.57}
✓ [20, 10, 15, 55] kl: {best: -0.48, worst: -0.56}
Pair #6
Original choice: Option 1
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
[10, 20, 40, 30] cosine_similarity: {best: 0.63, worst: 0.57}
✓ [20, 15, 10, 55] kl: {best: -0.48, worst: -0.56}
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
[10, 40, 30, 20] cosine_similarity: {best: 0.66, worst: 0.62}
✓ [20, 15, 15, 50] kl: {best: -0.41, worst: -0.52}
Pair #8
Original choice: Option 1
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
[10, 30, 40, 20] cosine_similarity: {best: 0.66, worst: 0.62}
✓ [20, 15, 15, 50] kl: {best: -0.41, worst: -0.52}
Pair #9
Original choice: Option 1
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
[10, 30, 25, 35] cosine_similarity: {best: 0.63, worst: 0.57}
✓ [20, 10, 15, 55] kl: {best: -0.48, worst: -0.55}
Pair #10
Original choice: Option 1
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
[10, 25, 30, 35] cosine_similarity: {best: 0.63, worst: 0.57}
✓ [20, 10, 15, 55] kl: {best: -0.48, worst: -0.55}