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User 09da82441a5b614abd0175e3ee34e9a4 Responses

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Survey Response Breakdown - Survey 182

User ID Submitted At Duration Ideal budget cosine_similaritykl View Response
09da82441... 09da82441a5b614abd0175e3ee34e9a4 23-07-2026 10:59 72s [45, 20, 25, 10] 90%10% View Response

User ID: 09da82441a5b614abd0175e3ee34e9a4

Survey ID: 182

Ideal budget: [45, 20, 25, 10]
⏱️ Response Time: 72s
Survey Summary
Choice Percentage
cosine_similarity (Rank) 90%
kl (Rank) 10%
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
✓ [50, 10, 10, 30] cosine_similarity: {best: 0.89, worst: 0.83}
[25, 45, 20, 10] kl: {best: -0.16, worst: -0.21}
Pair #2
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
✓ [60, 10, 10, 20] cosine_similarity: {best: 0.92, worst: 0.87}
[25, 20, 45, 10] kl: {best: -0.12, worst: -0.17}
Pair #3
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
✓ [55, 10, 10, 25] cosine_similarity: {best: 0.91, worst: 0.86}
[25, 15, 45, 15] kl: {best: -0.13, worst: -0.19}
Pair #4
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
✓ [60, 10, 10, 20] cosine_similarity: {best: 0.92, worst: 0.87}
[25, 40, 25, 10] kl: {best: -0.13, worst: -0.17}
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: 0.91, worst: 0.87}
[25, 40, 25, 10] kl: {best: -0.13, worst: -0.17}
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
✓ [55, 10, 10, 25] cosine_similarity: {best: 0.91, worst: 0.86}
[25, 40, 20, 15] kl: {best: -0.14, worst: -0.19}
Pair #7
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
✓ [55, 10, 10, 25] cosine_similarity: {best: 0.91, worst: 0.87}
[25, 40, 25, 10] kl: {best: -0.13, worst: -0.19}
Pair #8
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: 0.91, worst: 0.87}
[25, 20, 45, 10] kl: {best: -0.12, worst: -0.17}
Pair #9
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
[10, 35, 25, 30] cosine_similarity: {best: 0.69, worst: 0.64}
✓ [20, 15, 15, 50] kl: {best: -0.39, worst: -0.46}
Pair #10
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
✓ [55, 10, 10, 25] cosine_similarity: {best: 0.91, worst: 0.87}
[25, 20, 45, 10] kl: {best: -0.12, worst: -0.19}