{ "interpretation": "At bias ratio 0.1, fixed structured parameter-measurement bias makes the raw run nonfinite while same-RMS zero-mean noise remains trainable. The parameter-level affine predictor does not recover clean learning under online, 64-batch warm-up, or matched 1000-batch frozen calibration, so this adapter is closed rather than promoted.", "observations": { "clean_final_test_accuracy": 0.7905, "constant_cal1000_frozen_first_epoch_test_accuracy": 0.3605, "innovation_cal1000_frozen_first_epoch_test_accuracy": 0.3275, "innovation_cal64_online_final_test_accuracy": 0.5595, "innovation_online_final_test_accuracy": 0.6295, "raw_structured_bias_nonfinite": true, "same_rms_noise_final_test_accuracy": 0.685, "same_rms_noise_remains_finite": true }, "rows": { "clean": { "all_metrics_finite": true, "best_test_accuracy": 0.802, "epochs_completed": 10, "final_corrector": {}, "final_test_accuracy": 0.7905, "protocol": { "algorithm": "positive equilibrium propagation", "autodiff_used_for_learning": false, "batch_size": 128, "bias_ratio": 0.1, "dataset": "FashionMNIST", "device": "cuda", "epochs": 10, "inference_iterations": 30, "mode": "clean", "network": "author ConvHopfieldEnergy28 32-64-10", "neutral_cadence": 1, "predictor_rate": 0.5, "seed": 1988, "test_limit": 2000, "train_limit": 10000, "training_iterations": 12 } }, "constant_cal1000_frozen": { "all_metrics_finite": true, "best_test_accuracy": 0.3605, "epochs_completed": 1, "final_corrector": { "bias_rms": 0.3237730231776297, "bias_to_clean_rms": 26.431254436936896, "clean_rms": 0.012249627574435758, "neutral_observations": 1000, "residual_bias_rms": 0.4122399944579638, "residual_to_clean_rms": 33.65326757511257, "step": 78 }, "final_test_accuracy": 0.3605, "protocol": { "algorithm": "positive equilibrium propagation", "autodiff_used_for_learning": false, "batch_size": 128, "bias_ratio": 0.1, "calibration_batches": 1000, "calibration_observations": 1000, "calibration_seconds": 62.76313781738281, "dataset": "FashionMNIST", "determinism": "best_effort_warn_only", "device": "cuda", "epochs": 1, "inference_iterations": 30, "mode": "constant", "network": "author ConvHopfieldEnergy28 32-64-10", "neutral_cadence": 0, "predictor_rate": 0.5, "seed": 1988, "test_limit": 2000, "train_limit": 10000, "training_iterations": 12 } }, "innovation_cal1000_frozen": { "all_metrics_finite": true, "best_test_accuracy": 0.3275, "epochs_completed": 1, "final_corrector": { "bias_rms": 0.3237200042135343, "bias_to_clean_rms": 71.72440874952738, "clean_rms": 0.004513386863097249, "neutral_observations": 1000, "residual_bias_rms": 0.2362901873060857, "residual_to_clean_rms": 52.353187190325364, "step": 78 }, "final_test_accuracy": 0.3275, "protocol": { "algorithm": "positive equilibrium propagation", "autodiff_used_for_learning": false, "batch_size": 128, "bias_ratio": 0.1, "calibration_batches": 1000, "calibration_observations": 1000, "calibration_seconds": 63.849170207977295, "dataset": "FashionMNIST", "determinism": "best_effort_warn_only", "device": "cuda", "epochs": 1, "inference_iterations": 30, "mode": "innovation", "network": "author ConvHopfieldEnergy28 32-64-10", "neutral_cadence": 0, "predictor_rate": 0.5, "seed": 1988, "test_limit": 2000, "train_limit": 10000, "training_iterations": 12 } }, "innovation_cal64_online": { "all_metrics_finite": true, "best_test_accuracy": 0.6315, "epochs_completed": 10, "final_corrector": { "bias_rms": 0.32612410406317766, "neutral_observations": 854, "residual_bias_rms": 0.0003998780642494185, "step": 789 }, "final_test_accuracy": 0.5595, "protocol": { "algorithm": "positive equilibrium propagation", "autodiff_used_for_learning": false, "batch_size": 128, "bias_ratio": 0.1, "calibration_batches": 64, "calibration_observations": 64, "calibration_seconds": 4.21977424621582, "dataset": "FashionMNIST", "device": "cuda", "epochs": 10, "inference_iterations": 30, "mode": "innovation", "network": "author ConvHopfieldEnergy28 32-64-10", "neutral_cadence": 1, "predictor_rate": 0.5, "seed": 1988, "test_limit": 2000, "train_limit": 10000, "training_iterations": 12 } }, "innovation_online": { "all_metrics_finite": true, "best_test_accuracy": 0.6295, "epochs_completed": 10, "final_corrector": { "bias_rms": 0.3385132732724078, "neutral_observations": 790, "residual_bias_rms": 0.00048530249773301345, "step": 789 }, "final_test_accuracy": 0.6295, "protocol": { "algorithm": "positive equilibrium propagation", "autodiff_used_for_learning": false, "batch_size": 128, "bias_ratio": 0.1, "dataset": "FashionMNIST", "device": "cuda", "epochs": 10, "inference_iterations": 30, "mode": "innovation", "network": "author ConvHopfieldEnergy28 32-64-10", "neutral_cadence": 1, "predictor_rate": 0.5, "seed": 1988, "test_limit": 2000, "train_limit": 10000, "training_iterations": 12 } }, "oracle": { "all_metrics_finite": true, "best_test_accuracy": 0.7995, "epochs_completed": 10, "final_corrector": { "bias_rms": 0.15150278767133962, "neutral_observations": 0, "residual_bias_rms": 0.0, "step": 789 }, "final_test_accuracy": 0.739, "protocol": { "algorithm": "positive equilibrium propagation", "autodiff_used_for_learning": false, "batch_size": 128, "bias_ratio": 0.1, "dataset": "FashionMNIST", "device": "cuda", "epochs": 10, "inference_iterations": 30, "mode": "oracle", "network": "author ConvHopfieldEnergy28 32-64-10", "neutral_cadence": 1, "predictor_rate": 0.5, "seed": 1988, "test_limit": 2000, "train_limit": 10000, "training_iterations": 12 } }, "raw": { "all_metrics_finite": false, "best_test_accuracy": 0.1, "epochs_completed": 10, "final_corrector": { "bias_rms": null, "neutral_observations": 0, "residual_bias_rms": null, "step": 789 }, "final_test_accuracy": 0.1, "protocol": { "algorithm": "positive equilibrium propagation", "autodiff_used_for_learning": false, "batch_size": 128, "bias_ratio": 0.1, "calibration_batches": 0, "calibration_observations": 0, "calibration_seconds": 9.5367431640625e-07, "dataset": "FashionMNIST", "device": "cuda", "epochs": 10, "inference_iterations": 30, "mode": "raw", "network": "author ConvHopfieldEnergy28 32-64-10", "neutral_cadence": 1, "predictor_rate": 0.5, "seed": 1988, "test_limit": 2000, "train_limit": 10000, "training_iterations": 12 } }, "same_rms_noise": { "all_metrics_finite": true, "best_test_accuracy": 0.7035, "epochs_completed": 10, "final_corrector": { "bias_rms": 0.29874716964496195, "bias_to_clean_rms": 115.21319470829337, "clean_rms": 0.002592994408334528, "neutral_observations": 0, "residual_bias_rms": 0.29872960535884535, "residual_to_clean_rms": 115.20642096205614, "step": 789 }, "final_test_accuracy": 0.685, "protocol": { "algorithm": "positive equilibrium propagation", "autodiff_used_for_learning": false, "batch_size": 128, "bias_ratio": 0.1, "calibration_batches": 0, "calibration_observations": 0, "calibration_seconds": 9.5367431640625e-07, "dataset": "FashionMNIST", "device": "cuda", "epochs": 10, "inference_iterations": 30, "mode": "same_rms_noise", "network": "author ConvHopfieldEnergy28 32-64-10", "neutral_cadence": 1, "predictor_rate": 0.5, "seed": 1988, "test_limit": 2000, "train_limit": 10000, "training_iterations": 12 } } }, "stage": "rain_ep_parameter_measurement_s0", "status": "closed_negative_adapter_with_positive_bias_noise_control", "test_policy": "development_test_subset_observed_each_epoch" }