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User d81616a6de9972e09f95bd304bafe1bf Responses to survey 182

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User ID: d81616a6de9972e09f95bd304bafe1bf

Survey ID: 182

Ideal budget: [30, 35, 20, 15]
⏱️ Response Time: 295s
Survey Summary
Choice Percentage
cosine_similarity (Rank) 30%
kl (Rank) 70%
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, 45, 10, 35] cosine_similarity: {best: 0.84, worst: 0.80}
✓ [20, 20, 50, 10] kl: {best: -0.20, worst: -0.25}
Pair #2
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
[10, 50, 30, 10] cosine_similarity: {best: 0.89, worst: 0.86}
✓ [20, 25, 45, 10] kl: {best: -0.14, worst: -0.18}
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
✓ [10, 50, 10, 30] cosine_similarity: {best: 0.86, worst: 0.82}
[25, 15, 45, 15] kl: {best: -0.19, worst: -0.24}
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
[35, 10, 25, 30] cosine_similarity: {best: 0.84, worst: 0.80}
✓ [20, 20, 50, 10] kl: {best: -0.20, 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
[40, 10, 35, 15] cosine_similarity: {best: 0.84, worst: 0.80}
✓ [20, 20, 50, 10] kl: {best: -0.20, worst: -0.24}
Pair #6
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, 70, 10, 10] cosine_similarity: {best: 0.82, worst: 0.77}
✓ [20, 15, 50, 15] kl: {best: -0.23, worst: -0.29}
Pair #7
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, 40, 20, 30] cosine_similarity: {best: 0.89, worst: 0.86}
[20, 25, 45, 10] kl: {best: -0.14, worst: -0.18}
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, 45, 10, 35] cosine_similarity: {best: 0.84, worst: 0.81}
✓ [15, 20, 45, 20] kl: {best: -0.20, worst: -0.25}
Pair #9
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, 40, 25, 25] cosine_similarity: {best: 0.90, worst: 0.88}
[25, 20, 20, 35] kl: {best: -0.12, worst: -0.16}
Pair #10
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
[45, 10, 20, 25] cosine_similarity: {best: 0.84, worst: 0.80}
✓ [20, 20, 50, 10] kl: {best: -0.20, worst: -0.24}