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User 105d7927bf8e7cc5bb28bf1d73a20b80 Responses to survey 182

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User ID: 105d7927bf8e7cc5bb28bf1d73a20b80

Survey ID: 182

Ideal budget: [30, 25, 25, 20]
⏱️ Response Time: 69s
Survey Summary
Choice Percentage
cosine_similarity (Rank) 40%
kl (Rank) 60%
Pairs List
Pair #1
Original choice: Option 2
Pair Score: 0.15
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, 30, 10] cosine_similarity: {best: 0.89, worst: 0.86}
[20, 50, 15, 15] kl: {best: -0.13, worst: -0.17}
Pair #2
Original choice: Option 1
Pair Score: 0.15
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, 30, 10, 10] cosine_similarity: {best: 0.89, worst: 0.86}
[20, 50, 15, 15] kl: {best: -0.13, worst: -0.17}
Pair #3
Original choice: Option 1
Pair Score: 0.15
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, 30, 10, 10] cosine_similarity: {best: 0.89, worst: 0.86}
✓ [20, 15, 50, 15] kl: {best: -0.13, worst: -0.17}
Pair #4
Original choice: Option 2
Pair Score: 0.15
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, 30, 10] cosine_similarity: {best: 0.89, worst: 0.86}
[20, 15, 50, 15] kl: {best: -0.13, worst: -0.17}
Pair #5
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
[35, 45, 10, 10] cosine_similarity: {best: 0.89, worst: 0.85}
✓ [20, 20, 15, 45] kl: {best: -0.14, worst: -0.17}
Pair #6
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
[35, 10, 45, 10] cosine_similarity: {best: 0.89, worst: 0.85}
✓ [20, 20, 15, 45] kl: {best: -0.14, worst: -0.17}
Pair #7
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
[35, 10, 45, 10] cosine_similarity: {best: 0.89, worst: 0.85}
✓ [20, 15, 20, 45] kl: {best: -0.14, worst: -0.17}
Pair #8
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
[35, 45, 10, 10] cosine_similarity: {best: 0.89, worst: 0.85}
✓ [20, 15, 20, 45] kl: {best: -0.14, worst: -0.17}
Pair #9
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, 35, 10] cosine_similarity: {best: 0.90, worst: 0.88}
[15, 20, 25, 40] kl: {best: -0.13, worst: -0.16}
Pair #10
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, 35, 10, 10] cosine_similarity: {best: 0.90, worst: 0.88}
✓ [15, 20, 25, 40] kl: {best: -0.13, worst: -0.16}