Conformal Residual Gate for Latent Filtering / results.json
Beats tuned baseline
1{
2 "seed": 902,
3 "calibration_scores": 5000,
4 "alpha": [
5 0.05,
6 0.1,
7 0.2,
8 0.3
9 ],
10 "state_quantiles": {
11 "0.05": 0.5965198962191917,
12 "0.1": 0.49330205341989664,
13 "0.2": 0.37462588580248357,
14 "0.3": 0.3000014838535938
15 },
16 "state_coverage": {
17 "0.05": 0.9628,
18 "0.1": 0.9114666666666666,
19 "0.2": 0.8043333333333333,
20 "0.3": 0.6958666666666666
21 },
22 "residual_std": 0.18173619417383416,
23 "halfnormal_reference": {
24 "0.05": 0.3561963980777247,
25 "0.1": 0.29892950593160783,
26 "0.2": 0.23290438311586553,
27 "0.3": 0.18835738893616943
28 },
29 "calibration_size_sweep": {
30 "100": {
31 "q_mean": 0.5143648955220264,
32 "q_std": 0.06786245598644008,
33 "coverage_mean": 0.9157,
34 "coverage_std": 0.03941083607334409,
35 "predicted_q_std_scaling": 0.1
36 },
37 "500": {
38 "q_mean": 0.47992587196378367,
39 "q_std": 0.02437358037658826,
40 "coverage_mean": 0.9028400000000001,
41 "coverage_std": 0.020717683268164918,
42 "predicted_q_std_scaling": 0.044721359549995794
43 },
44 "2000": {
45 "q_mean": 0.47690253116970477,
46 "q_std": 0.015340505018111827,
47 "coverage_mean": 0.89901,
48 "coverage_std": 0.013596687096495218,
49 "predicted_q_std_scaling": 0.022360679774997897
50 },
51 "5000": {
52 "q_mean": 0.48130122153734967,
53 "q_std": 0.007485591613424923,
54 "coverage_mean": 0.9037099999999999,
55 "coverage_std": 0.007524752487623752,
56 "predicted_q_std_scaling": 0.01414213562373095
57 }
58 },
59 "innovation_threshold": 1.6344746423584564,
60 "contaminated_rmse_baseline": 0.38422296362424313,
61 "contaminated_rmse_gated": 0.3453084105090802,
62 "contaminated_rmse_improvement_fraction": 0.10128117473275244,
63 "trigger_rate": 0.1538,
64 "predictions": {
65 "coverage": "exchangeable marginal coverage is at least approximately 1-alpha",
66 "alpha_scaling": "q decreases with alpha and follows the half-normal reference",
67 "calibration_scaling": "quantile variability decreases approximately as m^(-1/2)",
68 "robust_intervention": "R inflation on innovation-triggered observations reduces error under outliers"
69 }
70}