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User 0a9d3ea6a37b9d53ede1dfdffb4695f7 Responses

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Survey Response Breakdown - Survey 157

User ID Submitted At Duration Ideal budget kll1 View Response
0a9d3ea6a... 0a9d3ea6a37b9d53ede1dfdffb4695f7 13-07-2026 19:13 238s [30, 30, 25, 15] 80%20% View Response

Survey Response Breakdown - Survey 182

User ID Submitted At Duration Ideal budget cosine_similaritykl View Response
0a9d3ea6a... 0a9d3ea6a37b9d53ede1dfdffb4695f7 23-07-2026 10:38 92s [30, 30, 20, 20] 100%0% View Response

User ID: 0a9d3ea6a37b9d53ede1dfdffb4695f7

Survey ID: 157

Ideal budget: [30, 30, 25, 15]
⏱️ Response Time: 238s
Survey Summary
Choice Percentage
kl (Rank) 80%
l1 (Rank) 20%
Pairs List
Pair #1
Original choice: Option 1
Pair Score: 0.20
Score = min(KL advantage, L1 advantage). Advantage = how much better one vector is than the other in each metric. Higher score = clearer choice.
Choice Option Type
✓ [55, 20, 15, 10] kl: {best: -0.13, worst: -0.20}
[30, 10, 25, 35] l1: {best: -40.00, worst: -50.00}
Pair #2
Original choice: Option 2
Pair Score: 0.20
Score = min(KL advantage, L1 advantage). Advantage = how much better one vector is than the other in each metric. Higher score = clearer choice.
Choice Option Type
✓ [55, 15, 20, 10] kl: {best: -0.14, worst: -0.20}
[30, 10, 25, 35] l1: {best: -40.00, worst: -50.00}
Pair #3
Original choice: Option 1
Pair Score: 0.20
Score = min(KL advantage, L1 advantage). Advantage = how much better one vector is than the other in each metric. Higher score = clearer choice.
Choice Option Type
✓ [45, 15, 15, 25] kl: {best: -0.14, worst: -0.20}
[30, 10, 25, 35] l1: {best: -40.00, worst: -50.00}
Pair #4
Original choice: Option 1
Pair Score: 0.20
Score = min(KL advantage, L1 advantage). Advantage = how much better one vector is than the other in each metric. Higher score = clearer choice.
Choice Option Type
✓ [50, 15, 15, 20] kl: {best: -0.14, worst: -0.20}
[30, 10, 25, 35] l1: {best: -40.00, worst: -50.00}
Pair #5
Original choice: Option 2
Pair Score: 0.20
Score = min(KL advantage, L1 advantage). Advantage = how much better one vector is than the other in each metric. Higher score = clearer choice.
Choice Option Type
✓ [15, 55, 20, 10] kl: {best: -0.14, worst: -0.20}
[10, 30, 25, 35] l1: {best: -40.00, worst: -50.00}
Pair #6
Original choice: Option 1
Pair Score: 0.20
Score = min(KL advantage, L1 advantage). Advantage = how much better one vector is than the other in each metric. Higher score = clearer choice.
Choice Option Type
[15, 20, 40, 25] kl: {best: -0.14, worst: -0.20}
✓ [30, 10, 25, 35] l1: {best: -40.00, worst: -50.00}
Pair #7
Original choice: Option 2
Pair Score: 0.20
Score = min(KL advantage, L1 advantage). Advantage = how much better one vector is than the other in each metric. Higher score = clearer choice.
Choice Option Type
[20, 55, 15, 10] kl: {best: -0.13, worst: -0.20}
✓ [30, 10, 25, 35] l1: {best: -40.00, worst: -50.00}
Pair #8
Original choice: Option 1
Pair Score: 0.20
Score = min(KL advantage, L1 advantage). Advantage = how much better one vector is than the other in each metric. Higher score = clearer choice.
Choice Option Type
✓ [15, 20, 35, 30] kl: {best: -0.14, worst: -0.20}
[30, 10, 25, 35] l1: {best: -40.00, worst: -50.00}
Pair #9
Original choice: Option 1
Pair Score: 0.20
Score = min(KL advantage, L1 advantage). Advantage = how much better one vector is than the other in each metric. Higher score = clearer choice.
Choice Option Type
✓ [20, 15, 35, 30] kl: {best: -0.14, worst: -0.20}
[10, 30, 25, 35] l1: {best: -40.00, worst: -50.00}
Pair #10
Original choice: Option 2
Pair Score: 0.20
Score = min(KL advantage, L1 advantage). Advantage = how much better one vector is than the other in each metric. Higher score = clearer choice.
Choice Option Type
✓ [20, 15, 45, 20] kl: {best: -0.14, worst: -0.20}
[10, 30, 25, 35] l1: {best: -40.00, worst: -50.00}

Survey ID: 182

Ideal budget: [30, 30, 20, 20]
⏱️ Response Time: 92s
Survey Summary
Choice Percentage
cosine_similarity (Rank) 50%
kl (Rank) 50%
Pairs List
Pair #1
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, 20, 35] cosine_similarity: {best: 0.88, worst: 0.85}
✓ [20, 20, 45, 15] kl: {best: -0.14, worst: -0.17}
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, 35, 35, 20] cosine_similarity: {best: 0.88, worst: 0.85}
✓ [20, 20, 45, 15] kl: {best: -0.14, worst: -0.17}
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
✓ [35, 10, 35, 20] cosine_similarity: {best: 0.88, worst: 0.85}
[20, 20, 45, 15] kl: {best: -0.14, worst: -0.17}
Pair #4
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, 20, 35] cosine_similarity: {best: 0.88, worst: 0.85}
✓ [20, 20, 45, 15] kl: {best: -0.14, worst: -0.17}
Pair #5
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, 35, 35, 20] cosine_similarity: {best: 0.88, worst: 0.85}
[20, 20, 15, 45] kl: {best: -0.14, worst: -0.17}
Pair #6
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, 20, 35] cosine_similarity: {best: 0.88, worst: 0.85}
[20, 20, 15, 45] kl: {best: -0.14, worst: -0.17}
Pair #7
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, 35, 20] cosine_similarity: {best: 0.88, worst: 0.85}
[20, 20, 15, 45] kl: {best: -0.14, 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
✓ [35, 10, 20, 35] cosine_similarity: {best: 0.88, worst: 0.85}
[20, 20, 15, 45] kl: {best: -0.14, worst: -0.17}
Pair #9
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
[30, 10, 25, 35] cosine_similarity: {best: 0.88, worst: 0.85}
✓ [20, 20, 45, 15] kl: {best: -0.14, worst: -0.17}
Pair #10
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, 30, 35, 25] cosine_similarity: {best: 0.88, worst: 0.85}
✓ [20, 20, 45, 15] kl: {best: -0.14, worst: -0.17}