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User 241be711172c08451ea33375e0181426 Responses

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Survey Response Breakdown - Survey 178

User ID Submitted At Duration Ideal budget cosine_similaritykl View Response
241be7111... 241be711172c08451ea33375e0181426 09-07-2026 13:08 120s [35, 30, 35] 60%40% View Response

User ID: 241be711172c08451ea33375e0181426

Survey ID: 178

Ideal budget: [35, 30, 35]
⏱️ Response Time: 120s
Survey Summary
Choice Percentage
cosine_similarity (Rank) 60%
kl (Rank) 40%
Pairs List
Pair #1
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
✓ [45, 10, 45] cosine_similarity: {best: 0.93, worst: 0.91}
[20, 50, 30] kl: {best: -0.10, worst: -0.15}
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
✓ [45, 10, 45] cosine_similarity: {best: 0.93, worst: 0.91}
[30, 50, 20] kl: {best: -0.10, worst: -0.15}
Pair #3
Original choice: Option 2
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
✓ [55, 35, 10] cosine_similarity: {best: 0.87, worst: 0.83}
[20, 60, 20] kl: {best: -0.18, worst: -0.23}
Pair #4
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, 35, 55] cosine_similarity: {best: 0.87, worst: 0.83}
✓ [20, 60, 20] kl: {best: -0.18, worst: -0.23}
Pair #5
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
✓ [35, 10, 55] cosine_similarity: {best: 0.90, worst: 0.88}
[20, 55, 25] kl: {best: -0.13, worst: -0.17}
Pair #6
Original choice: Option 2
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
✓ [35, 10, 55] cosine_similarity: {best: 0.90, worst: 0.88}
[25, 55, 20] kl: {best: -0.13, worst: -0.17}
Pair #7
Original choice: Option 2
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
✓ [55, 10, 35] cosine_similarity: {best: 0.90, worst: 0.88}
[25, 55, 20] kl: {best: -0.13, worst: -0.17}
Pair #8
Original choice: Option 2
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
[55, 10, 35] cosine_similarity: {best: 0.90, worst: 0.88}
✓ [20, 55, 25] kl: {best: -0.13, worst: -0.17}
Pair #9
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
[10, 50, 40] cosine_similarity: {best: 0.87, worst: 0.83}
✓ [20, 60, 20] kl: {best: -0.18, worst: -0.24}
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
[40, 50, 10] cosine_similarity: {best: 0.87, worst: 0.83}
✓ [20, 60, 20] kl: {best: -0.18, worst: -0.24}