{
  "schema_version": "maglab-standard-report-v3",
  "run": 100376,
  "generated_utc": "2026-08-21T13:57:26+00:00",
  "analyzer_version": "maglab-analyzer v16",
  "analysis_model_id": "maglab-analysis-v1",
  "run_header": {
    "run": 100376,
    "session_id": "63eacb65-d52f-4210-bc44-058ad5a86023",
    "started_utc_ms": 1787320167729,
    "duration_s": 300.293,
    "samples": {
      "calibrated": 15006,
      "uncalibrated": 15005,
      "accelerometer": 4739,
      "gyroscope": 16294
    },
    "magnetometer_accuracy_codes": "3\u00d715006",
    "requested_delay_us": 20000,
    "app_version": "38",
    "analysis_model_id": "maglab-analysis-v1",
    "has_console_manifest": false
  },
  "identity": {
    "person": "unknown",
    "role": "unassigned",
    "condition": "CONTROL"
  },
  "primary_outcome": {
    "version": "maglab-final-v1",
    "available": true,
    "reason": "",
    "stream": "calibrated",
    "nominal_hz": 50.0,
    "reference_n": 1500,
    "outcome_n": 3000,
    "reference_window_s": [
      0.0,
      30.0
    ],
    "outcome_window_s": [
      240.0,
      300.0
    ],
    "reference_actual_bounds_s": [
      0.0,
      29.980576184
    ],
    "outcome_actual_bounds_s": [
      240.00056914,
      299.980627834
    ],
    "run_seconds": 300.100593868,
    "signed_delta_nt": 652.8,
    "absolute_delta_nt": 652.8,
    "delta_pct": 0.816,
    "reference_magnitude_ut": 80.009441,
    "outcome_magnitude_ut": 80.662206,
    "angle_deg": 0.155,
    "ambient_ut": 80.29
  },
  "practitioner_comparison": {
    "available": false,
    "reason": "not_a_cherylee_primary_run"
  },
  "overall_quality": "COMPLETE WITH DATA-QUALITY WARNING",
  "summary": "CONTROL; +652.8 nT; complete with data-quality warning",
  "checks": {
    "readiness": {
      "status": "pass",
      "analyzable": true,
      "missing_streams": [],
      "session_type": "PHONE_FIRST_SESSION",
      "app_version": "38",
      "console_manifest": "unavailable_phone_first",
      "blocks": {
        "value": 1,
        "unit": "rows",
        "n": 1,
        "window": "whole run",
        "validity": "valid",
        "reason_code": "",
        "note": ""
      },
      "aborted_blocks": {
        "value": 0,
        "unit": "blocks",
        "n": 1,
        "window": "whole run",
        "validity": "valid",
        "reason_code": "",
        "note": ""
      },
      "streams": {
        "calibrated": {
          "value": 15006,
          "unit": "samples",
          "n": 15006,
          "window": "whole run",
          "validity": "valid",
          "reason_code": "",
          "note": ""
        },
        "uncalibrated": {
          "value": 15005,
          "unit": "samples",
          "n": 15005,
          "window": "whole run",
          "validity": "valid",
          "reason_code": "",
          "note": ""
        },
        "accelerometer": {
          "value": 4739,
          "unit": "samples",
          "n": 4739,
          "window": "whole run",
          "validity": "valid",
          "reason_code": "",
          "note": ""
        },
        "gyroscope": {
          "value": 16294,
          "unit": "samples",
          "n": 16294,
          "window": "whole run",
          "validity": "valid",
          "reason_code": "",
          "note": ""
        }
      }
    },
    "sampling": {
      "summary": "calibrated magnetometer 49.9999 Hz effective over N=15006 samples, 0 gaps",
      "stats": {
        "calibrated_samples": {
          "key": "calibrated_samples",
          "label": "calibrated samples",
          "value": 15006,
          "unit": "",
          "n": 15006,
          "window": [
            0.0,
            300.100593868
          ],
          "note": "",
          "validity": "valid",
          "reason_code": ""
        },
        "calibrated_duration": {
          "key": "calibrated_duration",
          "label": "calibrated span, first to last sample",
          "value": 300.101,
          "unit": "s",
          "n": 15006,
          "window": [
            0.0,
            300.100593868
          ],
          "note": "",
          "validity": "valid",
          "reason_code": ""
        },
        "calibrated_effective_rate": {
          "key": "calibrated_effective_rate",
          "label": "calibrated effective rate",
          "value": 49.99990105517748,
          "unit": "Hz",
          "n": 15006,
          "window": [
            0.0,
            300.100593868
          ],
          "note": "nominal 50 Hz",
          "validity": "valid",
          "reason_code": ""
        },
        "calibrated_median_interval": {
          "key": "calibrated_median_interval",
          "label": "calibrated median sample interval",
          "value": 19.999408999979096,
          "unit": "ms",
          "n": 15005,
          "window": [
            0.0,
            300.100593868
          ],
          "note": "",
          "validity": "valid",
          "reason_code": ""
        },
        "calibrated_max_interval": {
          "key": "calibrated_max_interval",
          "label": "calibrated largest sample interval",
          "value": 20.327494,
          "unit": "ms",
          "n": 15005,
          "window": [
            0.0,
            300.100593868
          ],
          "note": "",
          "validity": "valid",
          "reason_code": ""
        },
        "calibrated_gaps": {
          "key": "calibrated_gaps",
          "label": "calibrated intervals over 1.5\u00d7 nominal",
          "value": 0,
          "unit": "",
          "n": 15005,
          "window": [
            0.0,
            300.100593868
          ],
          "note": "",
          "validity": "valid",
          "reason_code": ""
        },
        "calibrated_missing_estimate": {
          "key": "calibrated_missing_estimate",
          "label": "calibrated samples missing across those gaps",
          "value": 0,
          "unit": "",
          "n": 15005,
          "window": [
            0.0,
            300.100593868
          ],
          "note": "estimated from interval length; the phone never fabricates a sample",
          "validity": "valid",
          "reason_code": ""
        },
        "calibrated_completeness": {
          "key": "calibrated_completeness",
          "label": "calibrated completeness against nominal rate",
          "value": 1.0001,
          "unit": "",
          "n": 15006,
          "window": [
            0.0,
            300.100593868
          ],
          "note": "",
          "validity": "valid",
          "reason_code": ""
        },
        "calibrated_gaps_exported": {
          "key": "calibrated_gaps_exported",
          "label": "calibrated gaps recorded by the phone",
          "value": 2,
          "unit": "",
          "n": 15005,
          "window": [
            0.0,
            300.100593868
          ],
          "note": "from data_gaps.csv",
          "validity": "valid",
          "reason_code": ""
        },
        "uncalibrated_samples": {
          "key": "uncalibrated_samples",
          "label": "uncalibrated samples",
          "value": 15005,
          "unit": "",
          "n": 15005,
          "window": [
            0.0,
            300.08059607
          ],
          "note": "",
          "validity": "valid",
          "reason_code": ""
        },
        "uncalibrated_duration": {
          "key": "uncalibrated_duration",
          "label": "uncalibrated span, first to last sample",
          "value": 300.081,
          "unit": "s",
          "n": 15005,
          "window": [
            0.0,
            300.08059607
          ],
          "note": "",
          "validity": "valid",
          "reason_code": ""
        },
        "uncalibrated_effective_rate": {
          "key": "uncalibrated_effective_rate",
          "label": "uncalibrated effective rate",
          "value": 49.99990068168222,
          "unit": "Hz",
          "n": 15005,
          "window": [
            0.0,
            300.08059607
          ],
          "note": "nominal 50 Hz",
          "validity": "valid",
          "reason_code": ""
        },
        "uncalibrated_median_interval": {
          "key": "uncalibrated_median_interval",
          "label": "uncalibrated median sample interval",
          "value": 19.99940949998802,
          "unit": "ms",
          "n": 15004,
          "window": [
            0.0,
            300.08059607
          ],
          "note": "",
          "validity": "valid",
          "reason_code": ""
        },
        "uncalibrated_max_interval": {
          "key": "uncalibrated_max_interval",
          "label": "uncalibrated largest sample interval",
          "value": 20.327494,
          "unit": "ms",
          "n": 15004,
          "window": [
            0.0,
            300.08059607
          ],
          "note": "",
          "validity": "valid",
          "reason_code": ""
        },
        "uncalibrated_gaps": {
          "key": "uncalibrated_gaps",
          "label": "uncalibrated intervals over 1.5\u00d7 nominal",
          "value": 0,
          "unit": "",
          "n": 15004,
          "window": [
            0.0,
            300.08059607
          ],
          "note": "",
          "validity": "valid",
          "reason_code": ""
        },
        "uncalibrated_missing_estimate": {
          "key": "uncalibrated_missing_estimate",
          "label": "uncalibrated samples missing across those gaps",
          "value": 0,
          "unit": "",
          "n": 15004,
          "window": [
            0.0,
            300.08059607
          ],
          "note": "estimated from interval length; the phone never fabricates a sample",
          "validity": "valid",
          "reason_code": ""
        },
        "uncalibrated_completeness": {
          "key": "uncalibrated_completeness",
          "label": "uncalibrated completeness against nominal rate",
          "value": 1.0001,
          "unit": "",
          "n": 15005,
          "window": [
            0.0,
            300.08059607
          ],
          "note": "",
          "validity": "valid",
          "reason_code": ""
        },
        "uncalibrated_gaps_exported": {
          "key": "uncalibrated_gaps_exported",
          "label": "uncalibrated gaps recorded by the phone",
          "value": 2,
          "unit": "",
          "n": 15004,
          "window": [
            0.0,
            300.08059607
          ],
          "note": "from data_gaps.csv",
          "validity": "valid",
          "reason_code": ""
        },
        "accelerometer_samples": {
          "key": "accelerometer_samples",
          "label": "accelerometer samples",
          "value": 4739,
          "unit": "",
          "n": 4739,
          "window": [
            0.0,
            300.073708373
          ],
          "note": "",
          "validity": "valid",
          "reason_code": ""
        },
        "accelerometer_duration": {
          "key": "accelerometer_duration",
          "label": "accelerometer span, first to last sample",
          "value": 300.074,
          "unit": "s",
          "n": 4739,
          "window": [
            0.0,
            300.073708373
          ],
          "note": "",
          "validity": "valid",
          "reason_code": ""
        },
        "accelerometer_effective_rate": {
          "key": "accelerometer_effective_rate",
          "label": "accelerometer effective rate",
          "value": 15.789453950129259,
          "unit": "Hz",
          "n": 4739,
          "window": [
            0.0,
            300.073708373
          ],
          "note": "nominal 50 Hz",
          "validity": "valid",
          "reason_code": ""
        },
        "accelerometer_median_interval": {
          "key": "accelerometer_median_interval",
          "label": "accelerometer median sample interval",
          "value": 80.22247099998481,
          "unit": "ms",
          "n": 4738,
          "window": [
            0.0,
            300.073708373
          ],
          "note": "",
          "validity": "valid",
          "reason_code": ""
        },
        "accelerometer_max_interval": {
          "key": "accelerometer_max_interval",
          "label": "accelerometer largest sample interval",
          "value": 80.22455500002934,
          "unit": "ms",
          "n": 4738,
          "window": [
            0.0,
            300.073708373
          ],
          "note": "",
          "validity": "valid",
          "reason_code": ""
        },
        "accelerometer_gaps": {
          "key": "accelerometer_gaps",
          "label": "accelerometer intervals over 1.5\u00d7 nominal",
          "value": 3408,
          "unit": "",
          "n": 4738,
          "window": [
            0.0,
            300.073708373
          ],
          "note": "",
          "validity": "valid",
          "reason_code": ""
        },
        "accelerometer_missing_estimate": {
          "key": "accelerometer_missing_estimate",
          "label": "accelerometer samples missing across those gaps",
          "value": 10224,
          "unit": "",
          "n": 4738,
          "window": [
            0.0,
            300.073708373
          ],
          "note": "estimated from interval length; the phone never fabricates a sample",
          "validity": "valid",
          "reason_code": ""
        },
        "accelerometer_completeness": {
          "key": "accelerometer_completeness",
          "label": "accelerometer completeness against nominal rate",
          "value": 0.3159,
          "unit": "",
          "n": 4739,
          "window": [
            0.0,
            300.073708373
          ],
          "note": "",
          "validity": "valid",
          "reason_code": ""
        },
        "accelerometer_gaps_exported": {
          "key": "accelerometer_gaps_exported",
          "label": "accelerometer gaps recorded by the phone",
          "value": 0,
          "unit": "",
          "n": 4738,
          "window": [
            0.0,
            300.073708373
          ],
          "note": "from data_gaps.csv",
          "validity": "valid",
          "reason_code": ""
        },
        "gyroscope_samples": {
          "key": "gyroscope_samples",
          "label": "gyroscope samples",
          "value": 16294,
          "unit": "",
          "n": 16294,
          "window": [
            0.0,
            300.093764405
          ],
          "note": "",
          "validity": "valid",
          "reason_code": ""
        },
        "gyroscope_duration": {
          "key": "gyroscope_duration",
          "label": "gyroscope span, first to last sample",
          "value": 300.094,
          "unit": "s",
          "n": 16294,
          "window": [
            0.0,
            300.093764405
          ],
          "note": "",
          "validity": "valid",
          "reason_code": ""
        },
        "gyroscope_effective_rate": {
          "key": "gyroscope_effective_rate",
          "label": "gyroscope effective rate",
          "value": 54.2930308208981,
          "unit": "Hz",
          "n": 16294,
          "window": [
            0.0,
            300.093764405
          ],
          "note": "nominal 50 Hz",
          "validity": "valid",
          "reason_code": ""
        },
        "gyroscope_median_interval": {
          "key": "gyroscope_median_interval",
          "label": "gyroscope median sample interval",
          "value": 20.055678000005628,
          "unit": "ms",
          "n": 16293,
          "window": [
            0.0,
            300.093764405
          ],
          "note": "",
          "validity": "valid",
          "reason_code": ""
        },
        "gyroscope_max_interval": {
          "key": "gyroscope_max_interval",
          "label": "gyroscope largest sample interval",
          "value": 20.056334999992487,
          "unit": "ms",
          "n": 16293,
          "window": [
            0.0,
            300.093764405
          ],
          "note": "",
          "validity": "valid",
          "reason_code": ""
        },
        "gyroscope_gaps": {
          "key": "gyroscope_gaps",
          "label": "gyroscope intervals over 1.5\u00d7 nominal",
          "value": 0,
          "unit": "",
          "n": 16293,
          "window": [
            0.0,
            300.093764405
          ],
          "note": "",
          "validity": "valid",
          "reason_code": ""
        },
        "gyroscope_missing_estimate": {
          "key": "gyroscope_missing_estimate",
          "label": "gyroscope samples missing across those gaps",
          "value": 0,
          "unit": "",
          "n": 16293,
          "window": [
            0.0,
            300.093764405
          ],
          "note": "estimated from interval length; the phone never fabricates a sample",
          "validity": "valid",
          "reason_code": ""
        },
        "gyroscope_completeness": {
          "key": "gyroscope_completeness",
          "label": "gyroscope completeness against nominal rate",
          "value": 1.0859,
          "unit": "",
          "n": 16294,
          "window": [
            0.0,
            300.093764405
          ],
          "note": "",
          "validity": "valid",
          "reason_code": ""
        },
        "gyroscope_gaps_exported": {
          "key": "gyroscope_gaps_exported",
          "label": "gyroscope gaps recorded by the phone",
          "value": 2,
          "unit": "",
          "n": 16293,
          "window": [
            0.0,
            300.093764405
          ],
          "note": "from data_gaps.csv",
          "validity": "valid",
          "reason_code": ""
        },
        "exported_gap_rows": {
          "key": "exported_gap_rows",
          "label": "Rows in data_gaps.csv",
          "value": 6,
          "unit": "",
          "n": 6,
          "window": "whole run",
          "note": "",
          "validity": "valid",
          "reason_code": ""
        }
      },
      "caveats": [
        "calibrated: this recount found 0 gaps but data_gaps.csv records 2. The two use different detection rules (here: interval > 1.5\u00d7 nominal), so a difference is expected for marginal intervals, but a large disagreement means the timing should be checked before use.",
        "uncalibrated: this recount found 0 gaps but data_gaps.csv records 2. The two use different detection rules (here: interval > 1.5\u00d7 nominal), so a difference is expected for marginal intervals, but a large disagreement means the timing should be checked before use.",
        "accelerometer: this recount found 3408 gaps but data_gaps.csv records 0. The two use different detection rules (here: interval > 1.5\u00d7 nominal), so a difference is expected for marginal intervals, but a large disagreement means the timing should be checked before use.",
        "gyroscope: this recount found 0 gaps but data_gaps.csv records 2. The two use different detection rules (here: interval > 1.5\u00d7 nominal), so a difference is expected for marginal intervals, but a large disagreement means the timing should be checked before use.",
        "Effective rate is (N\u22121)/span between the first and last sample, so a stream that stopped early reports a normal rate over a short span. Compare the span against the run duration."
      ],
      "per_block_calibrated_coverage": [
        {
          "block_index": 0,
          "n": 15005,
          "window_utc_ms": [
            1787320167880,
            1787320467980
          ],
          "effective_rate_hz": 49.99999999999999
        }
      ]
    },
    "warmup": {
      "status": "reported_unrecorded",
      "recorded_mask_s": [],
      "note": "Phone-first warm-up occurred before Room recording; CSV t=0 is the first measurement sample.",
      "app_version": "38"
    },
    "baseline_drift": {
      "summary": "calibrated |B| drifts 0.0019733 \u00b5T/s (0.592189 \u00b5T over 0.0\u2013300.1 s, N=15006)",
      "stats": {
        "calibrated_slope": {
          "key": "calibrated_slope",
          "label": "|B| slope, calibrated",
          "value": 0.001973301462098647,
          "unit": "\u00b5T/s",
          "n": 15006,
          "window": [
            0.0,
            300.100593868
          ],
          "note": "ordinary least squares on |B| against phone-clock time",
          "validity": "valid",
          "reason_code": ""
        },
        "calibrated_slope_stderr": {
          "key": "calibrated_slope_stderr",
          "label": "Slope standard error, calibrated",
          "value": 2.7552371810331038e-05,
          "unit": "\u00b5T/s",
          "n": 15006,
          "window": [
            0.0,
            300.100593868
          ],
          "note": "assumes independent residuals; sensor noise is autocorrelated, so this is optimistic",
          "validity": "valid",
          "reason_code": ""
        },
        "calibrated_total_change": {
          "key": "calibrated_total_change",
          "label": "Fitted change across the window, calibrated",
          "value": 0.5921889406563966,
          "unit": "\u00b5T",
          "n": 15006,
          "window": [
            0.0,
            300.100593868
          ],
          "note": "slope \u00d7 300.1 s",
          "validity": "valid",
          "reason_code": ""
        },
        "calibrated_residual_rms": {
          "key": "calibrated_residual_rms",
          "label": "Residual RMS after removing the slope, calibrated",
          "value": 0.2923931605115219,
          "unit": "\u00b5T",
          "n": 15006,
          "window": [
            0.0,
            300.100593868
          ],
          "note": "",
          "validity": "valid",
          "reason_code": ""
        },
        "calibrated_r_squared": {
          "key": "calibrated_r_squared",
          "label": "r\u00b2 of the linear fit, calibrated",
          "value": 0.254771696842252,
          "unit": "",
          "n": 15006,
          "window": [
            0.0,
            300.100593868
          ],
          "note": "fraction of |B| variance the straight line accounts for",
          "validity": "valid",
          "reason_code": ""
        },
        "calibrated_mean": {
          "key": "calibrated_mean",
          "label": "Mean |B|, calibrated",
          "value": 80.37238377968812,
          "unit": "\u00b5T",
          "n": 15006,
          "window": [
            0.0,
            300.100593868
          ],
          "note": "",
          "validity": "valid",
          "reason_code": ""
        },
        "calibrated_range": {
          "key": "calibrated_range",
          "label": "Peak-to-peak |B|, calibrated",
          "value": 1.898929999999993,
          "unit": "\u00b5T",
          "n": 15006,
          "window": [
            0.0,
            300.100593868
          ],
          "note": "",
          "validity": "valid",
          "reason_code": ""
        },
        "calibrated_slope_first_half": {
          "key": "calibrated_slope_first_half",
          "label": "Slope, first half, calibrated",
          "value": 0.004811886587218694,
          "unit": "\u00b5T/s",
          "n": 7503,
          "window": [
            0.0,
            150.040579822
          ],
          "note": "first vs second half",
          "validity": "valid",
          "reason_code": ""
        },
        "calibrated_slope_second_half": {
          "key": "calibrated_slope_second_half",
          "label": "Slope, second half, calibrated",
          "value": 0.0019298769792701301,
          "unit": "\u00b5T/s",
          "n": 7503,
          "window": [
            150.060578879,
            300.100593868
          ],
          "note": "first vs second half",
          "validity": "valid",
          "reason_code": ""
        },
        "uncalibrated_slope": {
          "key": "uncalibrated_slope",
          "label": "|B| slope, uncalibrated",
          "value": -0.0007258773963088463,
          "unit": "\u00b5T/s",
          "n": 15005,
          "window": [
            0.0,
            300.08059607
          ],
          "note": "ordinary least squares on |B| against phone-clock time",
          "validity": "valid",
          "reason_code": ""
        },
        "uncalibrated_slope_stderr": {
          "key": "uncalibrated_slope_stderr",
          "label": "Slope standard error, uncalibrated",
          "value": 1.6319234567481386e-05,
          "unit": "\u00b5T/s",
          "n": 15005,
          "window": [
            0.0,
            300.08059607
          ],
          "note": "assumes independent residuals; sensor noise is autocorrelated, so this is optimistic",
          "validity": "valid",
          "reason_code": ""
        },
        "uncalibrated_total_change": {
          "key": "uncalibrated_total_change",
          "label": "Fitted change across the window, uncalibrated",
          "value": -0.21782172175809822,
          "unit": "\u00b5T",
          "n": 15005,
          "window": [
            0.0,
            300.08059607
          ],
          "note": "slope \u00d7 300.1 s",
          "validity": "valid",
          "reason_code": ""
        },
        "uncalibrated_residual_rms": {
          "key": "uncalibrated_residual_rms",
          "label": "Residual RMS after removing the slope, uncalibrated",
          "value": 0.1731667828689581,
          "unit": "\u00b5T",
          "n": 15005,
          "window": [
            0.0,
            300.08059607
          ],
          "note": "",
          "validity": "valid",
          "reason_code": ""
        },
        "uncalibrated_r_squared": {
          "key": "uncalibrated_r_squared",
          "label": "r\u00b2 of the linear fit, uncalibrated",
          "value": 0.11650699049053526,
          "unit": "",
          "n": 15005,
          "window": [
            0.0,
            300.08059607
          ],
          "note": "fraction of |B| variance the straight line accounts for",
          "validity": "valid",
          "reason_code": ""
        },
        "uncalibrated_mean": {
          "key": "uncalibrated_mean",
          "label": "Mean |B|, uncalibrated",
          "value": 102.36372730896369,
          "unit": "\u00b5T",
          "n": 15005,
          "window": [
            0.0,
            300.08059607
          ],
          "note": "",
          "validity": "valid",
          "reason_code": ""
        },
        "uncalibrated_range": {
          "key": "uncalibrated_range",
          "label": "Peak-to-peak |B|, uncalibrated",
          "value": 1.0999960000000044,
          "unit": "\u00b5T",
          "n": 15005,
          "window": [
            0.0,
            300.08059607
          ],
          "note": "",
          "validity": "valid",
          "reason_code": ""
        },
        "uncalibrated_slope_first_half": {
          "key": "uncalibrated_slope_first_half",
          "label": "Slope, first half, uncalibrated",
          "value": -0.0018785833752845234,
          "unit": "\u00b5T/s",
          "n": 7502,
          "window": [
            0.0,
            150.020574679
          ],
          "note": "first vs second half",
          "validity": "valid",
          "reason_code": ""
        },
        "uncalibrated_slope_second_half": {
          "key": "uncalibrated_slope_second_half",
          "label": "Slope, second half, uncalibrated",
          "value": -0.0014258007472581372,
          "unit": "\u00b5T/s",
          "n": 7503,
          "window": [
            150.040579822,
            300.08059607
          ],
          "note": "first vs second half",
          "validity": "valid",
          "reason_code": ""
        }
      },
      "caveats": [
        "A drift is what the instrument reported over this window. It does not identify a cause; temperature, the phone's own bias estimate and a real field change all look like this."
      ]
    },
    "motion": {
      "status": "review",
      "derived_trips": 4,
      "derived_trip_intervals": [
        {
          "start_s": 0.0,
          "end_s": 10.220616683,
          "peak_gyro_deg_s": 3.1045687762400513,
          "peak_accel_dev_m_s2": 0.1736671364118898
        },
        {
          "start_s": 24.69898518,
          "end_s": 34.879488584,
          "peak_gyro_deg_s": 1.3755022424890864,
          "peak_accel_dev_m_s2": 0.08021536358810977
        },
        {
          "start_s": 157.437145216,
          "end_s": 178.547968012,
          "peak_gyro_deg_s": 2.550678443573387,
          "peak_accel_dev_m_s2": 0.15248686358810914
        },
        {
          "start_s": 293.635714346,
          "end_s": 303.675826418,
          "peak_gyro_deg_s": 1.0526426448767094,
          "peak_accel_dev_m_s2": 0.066747136411891
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      ],
      "exported_motion_gate_rows": 2,
      "orientation_artifact_channel": {
        "flagged": false,
        "perpendicular_sigma_nt": 9.552684155829228,
        "perpendicular_excursion_nt": 339.98058919188713,
        "n": 271,
        "window": [
          30.0,
          300.0
        ],
        "note": "Reported symmetrically as a diagnostic; it is not subtracted or used as a control."
      },
      "quiet_active_analysis": {
        "summary": "zero-lag r=0.0284879 (N=15005)",
        "stats": {
          "gyro_median_rate": {
            "key": "gyro_median_rate",
            "label": "Median |\u03c9| over the run",
            "value": 0.0009915265,
            "unit": "rad/s",
            "n": 16294,
            "window": "whole run",
            "note": "",
            "validity": "valid",
            "reason_code": ""
          },
          "gyro_p95_rate": {
            "key": "gyro_p95_rate",
            "label": "95th percentile |\u03c9|",
            "value": 0.003440249,
            "unit": "rad/s",
            "n": 16294,
            "window": "whole run",
            "note": "",
            "validity": "valid",
            "reason_code": ""
          },
          "gyro_max_rate": {
            "key": "gyro_max_rate",
            "label": "Maximum |\u03c9|",
            "value": 0.054184947,
            "unit": "rad/s",
            "n": 16294,
            "window": "whole run",
            "note": "",
            "validity": "valid",
            "reason_code": ""
          },
          "corr_pearson_lag0": {
            "key": "corr_pearson_lag0",
            "label": "Pearson r, |\u03c9| vs |\u0394B| at zero lag",
            "value": 0.02848794212381634,
            "unit": "",
            "n": 15005,
            "window": [
              0.019998656,
              300.100593868
            ],
            "note": "primary framing (a); no lag search involved",
            "validity": "valid",
            "reason_code": ""
          },
          "corr_p_lag0": {
            "key": "corr_p_lag0",
            "label": "p for zero-lag r, circular-shift null",
            "value": 0.015,
            "unit": "",
            "n": 15005,
            "window": [
              0.019998656,
              300.100593868
            ],
            "note": "999 circular shifts, two-sided; shifting preserves each series' autocorrelation",
            "validity": "valid",
            "reason_code": ""
          },
          "corr_spearman_lag0": {
            "key": "corr_spearman_lag0",
            "label": "Spearman \u03c1, |\u03c9| vs |\u0394B| at zero lag",
            "value": 0.004224873409192205,
            "unit": "",
            "n": 15005,
            "window": [
              0.019998656,
              300.100593868
            ],
            "note": "rank version, robust to the heavy tail in |\u0394B|",
            "validity": "valid",
            "reason_code": ""
          },
          "corr_r_squared_lag0": {
            "key": "corr_r_squared_lag0",
            "label": "r\u00b2 at zero lag (variance shared)",
            "value": 0.0008115628464499096,
            "unit": "",
            "n": 15005,
            "window": [
              0.019998656,
              300.100593868
            ],
            "note": "effect size for framing (a)",
            "validity": "valid",
            "reason_code": ""
          },
          "corr_best_lag_s": {
            "key": "corr_best_lag_s",
            "label": "Lag with the largest |r| (exploratory)",
            "value": 0.0,
            "unit": "s",
            "n": 15005,
            "window": [
              0.019998656,
              300.100593868
            ],
            "note": "21 lags tested from -1 to 1 s",
            "validity": "valid",
            "reason_code": ""
          },
          "corr_best_lag_r": {
            "key": "corr_best_lag_r",
            "label": "Pearson r at that lag (exploratory)",
            "value": 0.02848794212381634,
            "unit": "",
            "n": 15005,
            "window": [
              0.019998656,
              300.100593868
            ],
            "note": "selected out of 21 comparisons \u2014 not corrected, not a test",
            "validity": "valid",
            "reason_code": ""
          },
          "corr_lags_tested": {
            "key": "corr_lags_tested",
            "label": "Number of lags compared",
            "value": 21,
            "unit": "",
            "n": 15005,
            "window": [
              0.019998656,
              300.100593868
            ],
            "note": "",
            "validity": "valid",
            "reason_code": ""
          },
          "regime_comparison_possible": {
            "key": "regime_comparison_possible",
            "label": "Gyro-quiet vs gyro-active comparison possible",
            "value": false,
            "unit": "",
            "n": 16294,
            "window": "whole run",
            "note": "4 quiet and 0 active spans of at least 2 s at 0.02 rad/s",
            "validity": "valid",
            "reason_code": ""
          },
          "regime_peak_rate": {
            "key": "regime_peak_rate",
            "label": "Peak |\u03c9| against the threshold",
            "value": 0.054184947,
            "unit": "rad/s",
            "n": 16294,
            "window": "whole run",
            "note": "threshold 0.02 rad/s",
            "validity": "valid",
            "reason_code": ""
          }
        },
        "caveats": [
          "Regime framing skipped: the run has 4 quiet and 0 active spans of at least 2 s at a 0.02 rad/s threshold, so there is nothing to compare. Peak |\u03c9| in the whole run was 0.054185 rad/s. Lowering the threshold until a split appears would be choosing it from the data it then divides, so this analyzer does not do that; a run with deliberate phone movement is what would answer the question.",
          "21 exploratory comparisons were made in this run and none are corrected for multiplicity. The zero-lag correlation and the regime SD ratio are the two figures stated in advance; the best-lag number is a search result and should be treated as a hypothesis, not a finding.",
          "The quiet/active threshold is provisional (docs/analysis-model.md). Rerunning with a different threshold will change these numbers, and a threshold chosen after seeing the result is not a test.",
          "This measures the phone's magnetometer while the phone moves. It says nothing about the source of any field change, and it is not a pre-registered test of the pinwheel hypothesis."
        ]
      },
      "note": "Gyro quiet/active split and motion-gate trips are both reported; they use distinct established thresholds."
    },
    "thermal": {
      "status": "pass",
      "temperature_start_c": {
        "value": 29.0,
        "unit": "\u00b0C",
        "n": 1,
        "window": [
          0.0,
          0.0
        ],
        "validity": "valid",
        "reason_code": "",
        "note": ""
      },
      "temperature_end_c": {
        "value": 28.0,
        "unit": "\u00b0C",
        "n": 1,
        "window": [
          300.211,
          300.211
        ],
        "validity": "valid",
        "reason_code": "",
        "note": ""
      },
      "temperature_range_c": {
        "value": 1.0,
        "unit": "\u00b0C",
        "n": 31,
        "window": [
          0.0,
          300.211
        ],
        "validity": "valid",
        "reason_code": "",
        "note": ""
      },
      "temperature_slope_c_per_min": {
        "value": -0.29011915370196323,
        "unit": "\u00b0C/min",
        "n": 31,
        "window": [
          0.0,
          300.211
        ],
        "validity": "valid",
        "reason_code": "",
        "note": ""
      },
      "max_thermal_status": {
        "value": 0,
        "unit": "code",
        "n": 31,
        "window": "whole run",
        "validity": "valid",
        "reason_code": "",
        "note": ""
      },
      "estimated_sitting_elapsed_s": {
        "value": 360.293,
        "unit": "s",
        "n": null,
        "window": "warm-up + recording",
        "validity": "valid",
        "reason_code": "",
        "note": "Known Pixel 7 knee is approximately 7\u20138 minutes; association is not causation."
      },
      "charging_states": [
        "DISCHARGING"
      ],
      "screen_states": [
        "ON"
      ]
    },
    "ambient": {
      "status": "available",
      "reason_code": "",
      "install_id": "8a3bf1c7-e780-4fb1-8672-1f872174d348",
      "day_utc": "20260821",
      "rows_day": 30,
      "rows_context": 30,
      "ambient_control_windows": 1,
      "ambient_delta_mean_nt": -47810.81,
      "ambient_delta_median_nt": -47810.81,
      "ambient_windows_more_positive_fraction": 0.0,
      "window_utc_ms": [
        1787319867729,
        1787320768022
      ],
      "note": "Ambient context includes non-overlapping 300-second windows using the same 0\u201330 s versus 240\u2013300 s outcome."
    },
    "rolling_anomaly": {
      "version": "maglab-rolling-feedback-v1",
      "hop_s": 1,
      "window_lengths_s": [
        10,
        20,
        30
      ],
      "drift_sigma_nt": 208.70720716902974,
      "denominator_floor_nt": 1.0,
      "rows": 843,
      "valid_rows": 598,
      "top_candidate_windows": [
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          "score": 4.56690523019679,
          "valid": true,
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          "signed_change_nt": 953.1460360000068,
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        {
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          "score": 4.216650157592583,
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          "score": 4.185937159766816,
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          "signed_change_nt": 873.6352539999928,
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          "normalization_denominator_nt": 208.70720716902974
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        {
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          "score": 4.144327643172831,
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      ],
      "note": "Scores use feedback_meter level/drift_sigma. Both signs are treated symmetrically; ranked windows are descriptive."
    }
  }
}