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User cdf948bb29ac1abfecfbb3b2d94b0f53 Responses

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Survey Response Breakdown - Survey 178

User ID Submitted At Duration Ideal budget cosine_similaritykl View Response
cdf948bb2... cdf948bb29ac1abfecfbb3b2d94b0f53 09-07-2026 17:08 95s [70, 20, 10] 60%40% View Response

User ID: cdf948bb29ac1abfecfbb3b2d94b0f53

Survey ID: 178

Ideal budget: [70, 20, 10]
⏱️ Response Time: 95s
Survey Summary
Choice Percentage
cosine_similarity (Rank) 60%
kl (Rank) 40%
Pairs List
Pair #1
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
✓ [90, 5, 5] cosine_similarity: {best: 0.97, worst: 0.92}
[50, 40, 10] kl: {best: -0.10, worst: -0.17}
Pair #2
Original choice: Option 1
Pair Score: 0.09
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
[75, 5, 20] cosine_similarity: {best: 0.97, worst: 0.92}
✓ [50, 40, 10] kl: {best: -0.10, worst: -0.16}
Pair #3
Original choice: Option 1
Pair Score: 0.08
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
[90, 5, 5] cosine_similarity: {best: 0.97, worst: 0.94}
✓ [55, 40, 5] kl: {best: -0.10, worst: -0.17}
Pair #4
Original choice: Option 2
Pair Score: 0.08
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, 5, 25] cosine_similarity: {best: 0.96, worst: 0.90}
[45, 40, 15] kl: {best: -0.13, worst: -0.19}
Pair #5
Original choice: Option 1
Pair Score: 0.08
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
✓ [80, 5, 15] cosine_similarity: {best: 0.98, worst: 0.94}
[50, 35, 15] kl: {best: -0.08, worst: -0.14}
Pair #6
Original choice: Option 1
Pair Score: 0.08
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
✓ [65, 5, 30] cosine_similarity: {best: 0.94, worst: 0.88}
[45, 45, 10] kl: {best: -0.15, worst: -0.22}
Pair #7
Original choice: Option 1
Pair Score: 0.08
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
✓ [90, 5, 5] cosine_similarity: {best: 0.97, worst: 0.94}
[55, 15, 30] kl: {best: -0.12, worst: -0.17}
Pair #8
Original choice: Option 2
Pair Score: 0.07
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, 5, 45] cosine_similarity: {best: 0.82, worst: 0.75}
[35, 55, 10] kl: {best: -0.28, worst: -0.36}
Pair #9
Original choice: Option 2
Pair Score: 0.07
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
[85, 5, 10] cosine_similarity: {best: 0.98, worst: 0.94}
✓ [50, 35, 15] kl: {best: -0.08, worst: -0.14}
Pair #10
Original choice: Option 2
Pair Score: 0.07
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
[90, 5, 5] cosine_similarity: {best: 0.97, worst: 0.94}
✓ [50, 35, 15] kl: {best: -0.08, worst: -0.17}