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User 84d632796c6b0261f0f38a334ee46127 Responses to survey 182

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User ID: 84d632796c6b0261f0f38a334ee46127

Survey ID: 182

Ideal budget: [20, 30, 40, 10]
⏱️ Response Time: 210s
Survey Summary
Choice Percentage
cosine_similarity (Rank) 20%
kl (Rank) 80%
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
[10, 10, 55, 25] cosine_similarity: {best: 0.87, worst: 0.82}
✓ [45, 15, 25, 15] kl: {best: -0.19, worst: -0.25}
Pair #2
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
[10, 10, 60, 20] cosine_similarity: {best: 0.87, worst: 0.83}
✓ [45, 25, 20, 10] 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
[10, 10, 65, 15] cosine_similarity: {best: 0.87, worst: 0.83}
✓ [45, 25, 20, 10] kl: {best: -0.17, worst: -0.23}
Pair #4
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
[10, 10, 60, 20] cosine_similarity: {best: 0.87, worst: 0.83}
✓ [20, 20, 25, 35] kl: {best: -0.18, worst: -0.24}
Pair #5
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
[10, 10, 55, 25] cosine_similarity: {best: 0.87, worst: 0.83}
✓ [40, 20, 20, 20] 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
[10, 10, 70, 10] cosine_similarity: {best: 0.86, worst: 0.82}
✓ [45, 15, 25, 15] 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
✓ [10, 10, 45, 35] cosine_similarity: {best: 0.82, worst: 0.78}
[50, 20, 20, 10] kl: {best: -0.22, worst: -0.30}
Pair #8
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
✓ [10, 10, 55, 25] cosine_similarity: {best: 0.87, worst: 0.83}
[45, 25, 20, 10] kl: {best: -0.17, worst: -0.25}
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
[10, 10, 60, 20] cosine_similarity: {best: 0.87, worst: 0.83}
✓ [40, 20, 20, 20] 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
[10, 10, 55, 25] cosine_similarity: {best: 0.87, worst: 0.81}
✓ [45, 20, 20, 15] kl: {best: -0.20, worst: -0.25}