{
  "results_directory": "/workspace/pcanet-k100-audit/generated/vast-rerun",
  "raw_directory": "/workspace/pcanet-k100-audit/raw",
  "runs": {
    "100": {
      "correct": 9906,
      "total": 10000,
      "reference_prediction_matches": 9999,
      "median_task_ms": 297.2565030281354,
      "median_gross_mj": 43881.53333333334,
      "median_counter_above_idle_mj": 28777.896731818983,
      "median_sampled_above_idle_mj": 28291.346543889722
    }
  },
  "independent_accuracy_check": true,
  "idle_only_control_net_j": {
    "counter_net_j": 2.3781231650157224,
    "sampled_net_j": -0.4828730169026585
  },
  "feature_validation": {
    "images": 1536,
    "values": 3538944,
    "mismatched_values": 5976,
    "max_abs_difference": 0.008417937904596329,
    "nondefault_stream_checked": true
  },
  "checks": 322,
  "passed": true,
  "errors": [],
  "limitations": [
    "K=100: 1 predictions differ from the PyTorch feature reference. TF32/convolution arithmetic can cause threshold changes; this is not exact reference equivalence.",
    "Feature cross-check records differences. TF32 reference and the fused FP32-FMA convolution are not established as bitwise equivalent; raw feature arrays were not retained.",
    "Repeated-run stability, training-label perturbation, process monitoring and feature checks are retained scalar observations; this offline checker cannot replay them. Only the last measured prediction vector in each round was compared during execution.",
    "NVML energy counter and sampled-power integration share GPU sensors. Above-idle energy excludes host/platform power and the documented setup stages."
  ]
}