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      "machine": "x86_64",
      "python_major_minor": [
        3,
        12
      ],
      "torch": "2.10.0+cpu",
      "numpy": "2.2.6",
      "pyarrow": "21.0.0"
    },
    "original_precision_allowed": [
      "none",
      "ieee"
    ],
    "compute": {
      "provider": "Kaggle",
      "kernel": "sankalpsthakur/well-incremental-input-features-cpu",
      "jobs_max": 1,
      "max_seconds": 7200,
      "child_max_seconds": 6600,
      "included_cpu_only": true,
      "is_private": true,
      "gpu": false,
      "tpu": false,
      "internet": false,
      "paid_resource": false,
      "uses_reserved_study_budget": false,
      "image": "gcr.io/kaggle-images/python@sha256:dafd4ce5668bbf1ad422e4c109e0f18c9623c3a7c7f48b0235f13142755c40b9"
    },
    "inputs": {
      "reuse_validation_dataset": "sankalpsthakur/well-tcn-validation-stream-inputs",
      "reuse_validation_payload": "tcn-validation-stream.payload",
      "reuse_validation_payload_sha256": "9595ee4f09a21ec48dd4a365f55cf8ecb7dab8ff5e08663f6dab6d98415d2155",
      "reuse_validation_payload_bytes": 83159543,
      "dependency_dataset": "sankalpsthakur/tspulse-causal-preflight-cpu-inputs",
      "new_method_dataset": "sankalpsthakur/well-incremental-input-features-method",
      "new_method_payload_max_bytes": 1000000,
      "new_data_downloads": 0,
      "max_source_recordings": 33,
      "full_corpus_mounted": false,
      "training_consumed_or_reserved_raw_mounted": false,
      "original_archive_training_objects_and_reserved_support_metadata_disclosed": true
    },
    "timing": {
      "capture": "Every accepted per-row packet/update wall time, every grid feature wall time, every eligible model call and complete update-to-score wall time. Keep stage boundaries; decoder/acquisition excluded from packet timers and measured separately by recording.",
      "no_device_claim": "Linux host and process-lifetime RSS describe this retrospective harness; ring nbytes are persistent numeric buffer size, not total deployed process/model memory or target hardware deadline.",
      "output_limit_bytes": 700000000
    },
    "output_retention": {
      "all_grid_float_arrays": "Original raw/bin/fraction/normalized arrays plus lossless unsigned bitwise XOR to actual rolling arrays; dtype/shape/bit hashes bind reconstruction including NaNs and any failures. Encoding is storage only, never numeric scoring.",
      "all_grid_discrete_and_scores": "Exact ends/eligibility/channel masks/current availability, original and actual scores/alarms, every raw timing, recording offsets/groups and comparisons.",
      "source_redecode_for_review": "No local raw validation decoding; read-only saved-array reconstruction, source hashes and frozen arithmetic only.",
      "overwrite_policy": "Preserve original attempt and every setup/runner failure; no hidden recovery job or reuse of spent budget."
    },
    "authored_fixture_plan": [
      "Every-grid canonical features across >=1800 authored rows with random missing cells, changes, large offsets and all-missing channels",
      "Exact 539 cold warmup and 29+30n grid; first/last valid values, 64-tail/head and eight-sample bin orientation",
      "80% context/tail support boundaries and minimum pressure/scaler availability gates",
      "Future append/caller input/caller result/scaler mutation isolation",
      "Malformed keys, labels, bool/nonnumeric/nonfinite/oversized values, units/availability, duplicate/out-of-order/future/expired/regressed-clock packets remain atomic",
      "Accepted sequence/time gaps clear state and cold-warm; missing channels mask without hidden gap insertion",
      "Fresh restart cold state and recording reset prevent cross-history",
      "Original overflow/NaN behavior visible; stable centered variance with large-offset small-variation fixture",
      "Streaming frozen alarm replay including disabled threshold, support holes, two on/off and gap resets",
      "Source/model/runtime/dependency/path/role hash refusals before any raw decode/model execution; doubles only for precloud checks"
    ],
    "fits": 0,
    "retuning": false,
    "reserved_predictive_access": false,
    "source_authenticity_or_clock_calibration": false,
    "physical_calibration": false,
    "model_promoted": false,
    "field_qualified": false,
    "control_permission": false,
    "human_outreach": false,
    "independent_signoff": false
  },
  "presentation_model_predictions": 0,
  "live_telemetry": false,
  "field_qualified": false
}