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User 0c9ccef04463522084deba1252d82951 Responses to survey 182

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User ID: 0c9ccef04463522084deba1252d82951

Survey ID: 182

Ideal budget: [40, 30, 10, 20]
⏱️ Response Time: 63s
Survey Summary
Choice Percentage
cosine_similarity (Rank) 0%
kl (Rank) 100%
Pairs List
Pair #1
Original choice: Option 2
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
[55, 10, 25, 10] cosine_similarity: {best: 0.87, worst: 0.82}
✓ [25, 15, 15, 45] kl: {best: -0.19, worst: -0.25}
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
[60, 10, 20, 10] cosine_similarity: {best: 0.87, worst: 0.83}
✓ [20, 25, 10, 45] kl: {best: -0.17, worst: -0.24}
Pair #3
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
[65, 10, 15, 10] cosine_similarity: {best: 0.87, worst: 0.83}
✓ [20, 25, 10, 45] kl: {best: -0.17, worst: -0.23}
Pair #4
Original choice: Option 2
Pair Score: 0.12
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
[60, 10, 20, 10] cosine_similarity: {best: 0.87, worst: 0.83}
✓ [25, 20, 35, 20] kl: {best: -0.18, worst: -0.24}
Pair #5
Original choice: Option 2
Pair Score: 0.12
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
[55, 10, 25, 10] cosine_similarity: {best: 0.87, worst: 0.83}
✓ [20, 20, 20, 40] kl: {best: -0.19, worst: -0.25}
Pair #6
Original choice: Option 1
Pair Score: 0.12
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: 0.86, worst: 0.82}
✓ [25, 15, 15, 45] kl: {best: -0.19, worst: -0.24}
Pair #7
Original choice: Option 1
Pair Score: 0.12
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
[55, 10, 25, 10] cosine_similarity: {best: 0.87, worst: 0.83}
✓ [20, 25, 10, 45] kl: {best: -0.17, worst: -0.25}
Pair #8
Original choice: Option 2
Pair Score: 0.12
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: 0.82, worst: 0.78}
✓ [20, 20, 10, 50] kl: {best: -0.22, worst: -0.30}
Pair #9
Original choice: Option 1
Pair Score: 0.12
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
[60, 10, 20, 10] cosine_similarity: {best: 0.87, worst: 0.83}
✓ [20, 20, 20, 40] kl: {best: -0.19, worst: -0.24}
Pair #10
Original choice: Option 2
Pair Score: 0.12
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
[55, 10, 25, 10] cosine_similarity: {best: 0.87, worst: 0.81}
✓ [20, 20, 15, 45] kl: {best: -0.20, worst: -0.25}