{
  "schema_version": "maglab-standard-report-v3",
  "run": 100396,
  "generated_utc": "2026-08-21T21:35:41+00:00",
  "analyzer_version": "maglab-analyzer v16",
  "analysis_model_id": "maglab-analysis-v1",
  "run_header": {
    "run": 100396,
    "session_id": "bb25f4d6-01e5-4689-ab0b-a40ae75cfa6a",
    "started_utc_ms": 1787347733728,
    "duration_s": 300.303,
    "samples": {
      "calibrated": 15007,
      "uncalibrated": 15007,
      "accelerometer": 3743,
      "gyroscope": 14974
    },
    "magnetometer_accuracy_codes": "3\u00d715007",
    "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": 1501,
    "outcome_n": 3001,
    "reference_window_s": [
      0.0,
      30.0
    ],
    "outcome_window_s": [
      240.0,
      300.0
    ],
    "reference_actual_bounds_s": [
      0.0,
      29.999987962
    ],
    "outcome_actual_bounds_s": [
      240.000001939,
      299.999988182
    ],
    "run_seconds": 300.119984264,
    "signed_delta_nt": 330.6,
    "absolute_delta_nt": 330.6,
    "delta_pct": 0.642,
    "reference_magnitude_ut": 51.452252,
    "outcome_magnitude_ut": 51.782806,
    "angle_deg": 0.449,
    "ambient_ut": 51.8
  },
  "practitioner_comparison": {
    "available": false,
    "reason": "not_a_cherylee_primary_run"
  },
  "overall_quality": "COMPLETE WITH DATA-QUALITY WARNING",
  "summary": "CONTROL; +330.6 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": 15007,
          "unit": "samples",
          "n": 15007,
          "window": "whole run",
          "validity": "valid",
          "reason_code": "",
          "note": ""
        },
        "uncalibrated": {
          "value": 15007,
          "unit": "samples",
          "n": 15007,
          "window": "whole run",
          "validity": "valid",
          "reason_code": "",
          "note": ""
        },
        "accelerometer": {
          "value": 3743,
          "unit": "samples",
          "n": 3743,
          "window": "whole run",
          "validity": "valid",
          "reason_code": "",
          "note": ""
        },
        "gyroscope": {
          "value": 14974,
          "unit": "samples",
          "n": 14974,
          "window": "whole run",
          "validity": "valid",
          "reason_code": "",
          "note": ""
        }
      }
    },
    "sampling": {
      "summary": "calibrated magnetometer 50 Hz effective over N=15007 samples, 0 gaps",
      "stats": {
        "calibrated_samples": {
          "key": "calibrated_samples",
          "label": "calibrated samples",
          "value": 15007,
          "unit": "",
          "n": 15007,
          "window": [
            0.0,
            300.119984264
          ],
          "note": "",
          "validity": "valid",
          "reason_code": ""
        },
        "calibrated_duration": {
          "key": "calibrated_duration",
          "label": "calibrated span, first to last sample",
          "value": 300.12,
          "unit": "s",
          "n": 15007,
          "window": [
            0.0,
            300.119984264
          ],
          "note": "",
          "validity": "valid",
          "reason_code": ""
        },
        "calibrated_effective_rate": {
          "key": "calibrated_effective_rate",
          "label": "calibrated effective rate",
          "value": 50.00000262161816,
          "unit": "Hz",
          "n": 15007,
          "window": [
            0.0,
            300.119984264
          ],
          "note": "nominal 50 Hz",
          "validity": "valid",
          "reason_code": ""
        },
        "calibrated_median_interval": {
          "key": "calibrated_median_interval",
          "label": "calibrated median sample interval",
          "value": 19.999548000001255,
          "unit": "ms",
          "n": 15006,
          "window": [
            0.0,
            300.119984264
          ],
          "note": "",
          "validity": "valid",
          "reason_code": ""
        },
        "calibrated_max_interval": {
          "key": "calibrated_max_interval",
          "label": "calibrated largest sample interval",
          "value": 20.311498000012307,
          "unit": "ms",
          "n": 15006,
          "window": [
            0.0,
            300.119984264
          ],
          "note": "",
          "validity": "valid",
          "reason_code": ""
        },
        "calibrated_gaps": {
          "key": "calibrated_gaps",
          "label": "calibrated intervals over 1.5\u00d7 nominal",
          "value": 0,
          "unit": "",
          "n": 15006,
          "window": [
            0.0,
            300.119984264
          ],
          "note": "",
          "validity": "valid",
          "reason_code": ""
        },
        "calibrated_missing_estimate": {
          "key": "calibrated_missing_estimate",
          "label": "calibrated samples missing across those gaps",
          "value": 0,
          "unit": "",
          "n": 15006,
          "window": [
            0.0,
            300.119984264
          ],
          "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": 15007,
          "window": [
            0.0,
            300.119984264
          ],
          "note": "",
          "validity": "valid",
          "reason_code": ""
        },
        "calibrated_gaps_exported": {
          "key": "calibrated_gaps_exported",
          "label": "calibrated gaps recorded by the phone",
          "value": 1,
          "unit": "",
          "n": 15006,
          "window": [
            0.0,
            300.119984264
          ],
          "note": "from data_gaps.csv",
          "validity": "valid",
          "reason_code": ""
        },
        "uncalibrated_samples": {
          "key": "uncalibrated_samples",
          "label": "uncalibrated samples",
          "value": 15007,
          "unit": "",
          "n": 15007,
          "window": [
            0.0,
            300.119984264
          ],
          "note": "",
          "validity": "valid",
          "reason_code": ""
        },
        "uncalibrated_duration": {
          "key": "uncalibrated_duration",
          "label": "uncalibrated span, first to last sample",
          "value": 300.12,
          "unit": "s",
          "n": 15007,
          "window": [
            0.0,
            300.119984264
          ],
          "note": "",
          "validity": "valid",
          "reason_code": ""
        },
        "uncalibrated_effective_rate": {
          "key": "uncalibrated_effective_rate",
          "label": "uncalibrated effective rate",
          "value": 50.00000262161816,
          "unit": "Hz",
          "n": 15007,
          "window": [
            0.0,
            300.119984264
          ],
          "note": "nominal 50 Hz",
          "validity": "valid",
          "reason_code": ""
        },
        "uncalibrated_median_interval": {
          "key": "uncalibrated_median_interval",
          "label": "uncalibrated median sample interval",
          "value": 19.999548000001255,
          "unit": "ms",
          "n": 15006,
          "window": [
            0.0,
            300.119984264
          ],
          "note": "",
          "validity": "valid",
          "reason_code": ""
        },
        "uncalibrated_max_interval": {
          "key": "uncalibrated_max_interval",
          "label": "uncalibrated largest sample interval",
          "value": 20.311498000012307,
          "unit": "ms",
          "n": 15006,
          "window": [
            0.0,
            300.119984264
          ],
          "note": "",
          "validity": "valid",
          "reason_code": ""
        },
        "uncalibrated_gaps": {
          "key": "uncalibrated_gaps",
          "label": "uncalibrated intervals over 1.5\u00d7 nominal",
          "value": 0,
          "unit": "",
          "n": 15006,
          "window": [
            0.0,
            300.119984264
          ],
          "note": "",
          "validity": "valid",
          "reason_code": ""
        },
        "uncalibrated_missing_estimate": {
          "key": "uncalibrated_missing_estimate",
          "label": "uncalibrated samples missing across those gaps",
          "value": 0,
          "unit": "",
          "n": 15006,
          "window": [
            0.0,
            300.119984264
          ],
          "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": 15007,
          "window": [
            0.0,
            300.119984264
          ],
          "note": "",
          "validity": "valid",
          "reason_code": ""
        },
        "uncalibrated_gaps_exported": {
          "key": "uncalibrated_gaps_exported",
          "label": "uncalibrated gaps recorded by the phone",
          "value": 1,
          "unit": "",
          "n": 15006,
          "window": [
            0.0,
            300.119984264
          ],
          "note": "from data_gaps.csv",
          "validity": "valid",
          "reason_code": ""
        },
        "accelerometer_samples": {
          "key": "accelerometer_samples",
          "label": "accelerometer samples",
          "value": 3743,
          "unit": "",
          "n": 3743,
          "window": [
            0.0,
            300.012318174
          ],
          "note": "",
          "validity": "valid",
          "reason_code": ""
        },
        "accelerometer_duration": {
          "key": "accelerometer_duration",
          "label": "accelerometer span, first to last sample",
          "value": 300.012,
          "unit": "s",
          "n": 3743,
          "window": [
            0.0,
            300.012318174
          ],
          "note": "",
          "validity": "valid",
          "reason_code": ""
        },
        "accelerometer_effective_rate": {
          "key": "accelerometer_effective_rate",
          "label": "accelerometer effective rate",
          "value": 12.472821192060952,
          "unit": "Hz",
          "n": 3743,
          "window": [
            0.0,
            300.012318174
          ],
          "note": "nominal 50 Hz",
          "validity": "valid",
          "reason_code": ""
        },
        "accelerometer_median_interval": {
          "key": "accelerometer_median_interval",
          "label": "accelerometer median sample interval",
          "value": 80.1741490000012,
          "unit": "ms",
          "n": 3742,
          "window": [
            0.0,
            300.012318174
          ],
          "note": "",
          "validity": "valid",
          "reason_code": ""
        },
        "accelerometer_max_interval": {
          "key": "accelerometer_max_interval",
          "label": "accelerometer largest sample interval",
          "value": 80.17603100000001,
          "unit": "ms",
          "n": 3742,
          "window": [
            0.0,
            300.012318174
          ],
          "note": "",
          "validity": "valid",
          "reason_code": ""
        },
        "accelerometer_gaps": {
          "key": "accelerometer_gaps",
          "label": "accelerometer intervals over 1.5\u00d7 nominal",
          "value": 3742,
          "unit": "",
          "n": 3742,
          "window": [
            0.0,
            300.012318174
          ],
          "note": "",
          "validity": "valid",
          "reason_code": ""
        },
        "accelerometer_missing_estimate": {
          "key": "accelerometer_missing_estimate",
          "label": "accelerometer samples missing across those gaps",
          "value": 11226,
          "unit": "",
          "n": 3742,
          "window": [
            0.0,
            300.012318174
          ],
          "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": 0.2495,
          "unit": "",
          "n": 3743,
          "window": [
            0.0,
            300.012318174
          ],
          "note": "",
          "validity": "valid",
          "reason_code": ""
        },
        "accelerometer_gaps_exported": {
          "key": "accelerometer_gaps_exported",
          "label": "accelerometer gaps recorded by the phone",
          "value": 1,
          "unit": "",
          "n": 3742,
          "window": [
            0.0,
            300.012318174
          ],
          "note": "from data_gaps.csv",
          "validity": "valid",
          "reason_code": ""
        },
        "gyroscope_samples": {
          "key": "gyroscope_samples",
          "label": "gyroscope samples",
          "value": 14974,
          "unit": "",
          "n": 14974,
          "window": [
            0.0,
            300.112537859
          ],
          "note": "",
          "validity": "valid",
          "reason_code": ""
        },
        "gyroscope_duration": {
          "key": "gyroscope_duration",
          "label": "gyroscope span, first to last sample",
          "value": 300.113,
          "unit": "s",
          "n": 14974,
          "window": [
            0.0,
            300.112537859
          ],
          "note": "",
          "validity": "valid",
          "reason_code": ""
        },
        "gyroscope_effective_rate": {
          "key": "gyroscope_effective_rate",
          "label": "gyroscope effective rate",
          "value": 49.89128447220913,
          "unit": "Hz",
          "n": 14974,
          "window": [
            0.0,
            300.112537859
          ],
          "note": "nominal 50 Hz",
          "validity": "valid",
          "reason_code": ""
        },
        "gyroscope_median_interval": {
          "key": "gyroscope_median_interval",
          "label": "gyroscope median sample interval",
          "value": 20.043603999994275,
          "unit": "ms",
          "n": 14973,
          "window": [
            0.0,
            300.112537859
          ],
          "note": "",
          "validity": "valid",
          "reason_code": ""
        },
        "gyroscope_max_interval": {
          "key": "gyroscope_max_interval",
          "label": "gyroscope largest sample interval",
          "value": 20.044305999999956,
          "unit": "ms",
          "n": 14973,
          "window": [
            0.0,
            300.112537859
          ],
          "note": "",
          "validity": "valid",
          "reason_code": ""
        },
        "gyroscope_gaps": {
          "key": "gyroscope_gaps",
          "label": "gyroscope intervals over 1.5\u00d7 nominal",
          "value": 0,
          "unit": "",
          "n": 14973,
          "window": [
            0.0,
            300.112537859
          ],
          "note": "",
          "validity": "valid",
          "reason_code": ""
        },
        "gyroscope_missing_estimate": {
          "key": "gyroscope_missing_estimate",
          "label": "gyroscope samples missing across those gaps",
          "value": 0,
          "unit": "",
          "n": 14973,
          "window": [
            0.0,
            300.112537859
          ],
          "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": 0.9979,
          "unit": "",
          "n": 14974,
          "window": [
            0.0,
            300.112537859
          ],
          "note": "",
          "validity": "valid",
          "reason_code": ""
        },
        "gyroscope_gaps_exported": {
          "key": "gyroscope_gaps_exported",
          "label": "gyroscope gaps recorded by the phone",
          "value": 1,
          "unit": "",
          "n": 14973,
          "window": [
            0.0,
            300.112537859
          ],
          "note": "from data_gaps.csv",
          "validity": "valid",
          "reason_code": ""
        },
        "exported_gap_rows": {
          "key": "exported_gap_rows",
          "label": "Rows in data_gaps.csv",
          "value": 4,
          "unit": "",
          "n": 4,
          "window": "whole run",
          "note": "",
          "validity": "valid",
          "reason_code": ""
        }
      },
      "caveats": [
        "calibrated: this recount found 0 gaps but data_gaps.csv records 1. 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 1. 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 3742 gaps but data_gaps.csv records 1. 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 1. 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": 15007,
          "window_utc_ms": [
            1787347733869,
            1787348033997
          ],
          "effective_rate_hz": 50.0019991470306
        }
      ]
    },
    "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 0.00154789 \u00b5T/s (0.464553 \u00b5T over 0.0\u2013300.1 s, N=15007)",
      "stats": {
        "calibrated_slope": {
          "key": "calibrated_slope",
          "label": "|B| slope, calibrated",
          "value": 0.0015478920847105785,
          "unit": "\u00b5T/s",
          "n": 15007,
          "window": [
            0.0,
            300.119984264
          ],
          "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": 1.563403749447083e-05,
          "unit": "\u00b5T/s",
          "n": 15007,
          "window": [
            0.0,
            300.119984264
          ],
          "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": 0.464553348105709,
          "unit": "\u00b5T",
          "n": 15007,
          "window": [
            0.0,
            300.119984264
          ],
          "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": 0.16592904379255202,
          "unit": "\u00b5T",
          "n": 15007,
          "window": [
            0.0,
            300.119984264
          ],
          "note": "",
          "validity": "valid",
          "reason_code": ""
        },
        "calibrated_r_squared": {
          "key": "calibrated_r_squared",
          "label": "r\u00b2 of the linear fit, calibrated",
          "value": 0.39514381399407494,
          "unit": "",
          "n": 15007,
          "window": [
            0.0,
            300.119984264
          ],
          "note": "fraction of |B| variance the straight line accounts for",
          "validity": "valid",
          "reason_code": ""
        },
        "calibrated_mean": {
          "key": "calibrated_mean",
          "label": "Mean |B|, calibrated",
          "value": 51.75033090284535,
          "unit": "\u00b5T",
          "n": 15007,
          "window": [
            0.0,
            300.119984264
          ],
          "note": "",
          "validity": "valid",
          "reason_code": ""
        },
        "calibrated_range": {
          "key": "calibrated_range",
          "label": "Peak-to-peak |B|, calibrated",
          "value": 0.9107400000000041,
          "unit": "\u00b5T",
          "n": 15007,
          "window": [
            0.0,
            300.119984264
          ],
          "note": "",
          "validity": "valid",
          "reason_code": ""
        },
        "calibrated_slope_first_half": {
          "key": "calibrated_slope_first_half",
          "label": "Slope, first half, calibrated",
          "value": 0.004328798459028803,
          "unit": "\u00b5T/s",
          "n": 7503,
          "window": [
            0.0,
            150.039991681
          ],
          "note": "first vs second half",
          "validity": "valid",
          "reason_code": ""
        },
        "calibrated_slope_second_half": {
          "key": "calibrated_slope_second_half",
          "label": "Slope, second half, calibrated",
          "value": -0.001655426247411395,
          "unit": "\u00b5T/s",
          "n": 7504,
          "window": [
            150.05998642,
            300.119984264
          ],
          "note": "first vs second half",
          "validity": "valid",
          "reason_code": ""
        },
        "uncalibrated_slope": {
          "key": "uncalibrated_slope",
          "label": "|B| slope, uncalibrated",
          "value": -0.00042437363202184537,
          "unit": "\u00b5T/s",
          "n": 15007,
          "window": [
            0.0,
            300.119984264
          ],
          "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": 2.0822440825414873e-05,
          "unit": "\u00b5T/s",
          "n": 15007,
          "window": [
            0.0,
            300.119984264
          ],
          "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": -0.12736300776445275,
          "unit": "\u00b5T",
          "n": 15007,
          "window": [
            0.0,
            300.119984264
          ],
          "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": 0.22099522895541154,
          "unit": "\u00b5T",
          "n": 15007,
          "window": [
            0.0,
            300.119984264
          ],
          "note": "",
          "validity": "valid",
          "reason_code": ""
        },
        "uncalibrated_r_squared": {
          "key": "uncalibrated_r_squared",
          "label": "r\u00b2 of the linear fit, uncalibrated",
          "value": 0.026936350800232156,
          "unit": "",
          "n": 15007,
          "window": [
            0.0,
            300.119984264
          ],
          "note": "fraction of |B| variance the straight line accounts for",
          "validity": "valid",
          "reason_code": ""
        },
        "uncalibrated_mean": {
          "key": "uncalibrated_mean",
          "label": "Mean |B|, uncalibrated",
          "value": 211.53572738921838,
          "unit": "\u00b5T",
          "n": 15007,
          "window": [
            0.0,
            300.119984264
          ],
          "note": "",
          "validity": "valid",
          "reason_code": ""
        },
        "uncalibrated_range": {
          "key": "uncalibrated_range",
          "label": "Peak-to-peak |B|, uncalibrated",
          "value": 1.4280399999999815,
          "unit": "\u00b5T",
          "n": 15007,
          "window": [
            0.0,
            300.119984264
          ],
          "note": "",
          "validity": "valid",
          "reason_code": ""
        },
        "uncalibrated_slope_first_half": {
          "key": "uncalibrated_slope_first_half",
          "label": "Slope, first half, uncalibrated",
          "value": 0.0034114391285634815,
          "unit": "\u00b5T/s",
          "n": 7503,
          "window": [
            0.0,
            150.039991681
          ],
          "note": "first vs second half",
          "validity": "valid",
          "reason_code": ""
        },
        "uncalibrated_slope_second_half": {
          "key": "uncalibrated_slope_second_half",
          "label": "Slope, second half, uncalibrated",
          "value": -0.003214821358497392,
          "unit": "\u00b5T/s",
          "n": 7504,
          "window": [
            150.05998642,
            300.119984264
          ],
          "note": "first vs second half",
          "validity": "valid",
          "reason_code": ""
        }
      },
      "caveats": [
        "calibrated: the two halves drift in opposite directions, so the whole-run slope understates what the field actually did. Treat the single slope as a summary, not a description.",
        "uncalibrated: the two halves drift in opposite directions, so the whole-run slope understates what the field actually did. Treat the single slope as a summary, not a description.",
        "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": 1,
      "derived_trip_intervals": [
        {
          "start_s": 190.393702535,
          "end_s": 200.694354456,
          "peak_gyro_deg_s": 20.23767719451181,
          "peak_accel_dev_m_s2": 0.09105855577822375
        }
      ],
      "exported_motion_gate_rows": 1,
      "orientation_artifact_channel": {
        "flagged": false,
        "perpendicular_sigma_nt": 57.945065320626505,
        "perpendicular_excursion_nt": 431.02960244443176,
        "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=-0.00643707 (N=15006)",
        "stats": {
          "gyro_median_rate": {
            "key": "gyro_median_rate",
            "label": "Median |\u03c9| over the run",
            "value": 0.0011828197,
            "unit": "rad/s",
            "n": 14974,
            "window": "whole run",
            "note": "",
            "validity": "valid",
            "reason_code": ""
          },
          "gyro_p95_rate": {
            "key": "gyro_p95_rate",
            "label": "95th percentile |\u03c9|",
            "value": 0.0022551676,
            "unit": "rad/s",
            "n": 14974,
            "window": "whole run",
            "note": "",
            "validity": "valid",
            "reason_code": ""
          },
          "gyro_max_rate": {
            "key": "gyro_max_rate",
            "label": "Maximum |\u03c9|",
            "value": 0.3532141,
            "unit": "rad/s",
            "n": 14974,
            "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": -0.006437071865489661,
            "unit": "",
            "n": 15006,
            "window": [
              0.020001589,
              300.119984264
            ],
            "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": 0.44,
            "unit": "",
            "n": 15006,
            "window": [
              0.020001589,
              300.119984264
            ],
            "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": 0.009318267954778909,
            "unit": "",
            "n": 15006,
            "window": [
              0.020001589,
              300.119984264
            ],
            "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": 4.143589420147854e-05,
            "unit": "",
            "n": 15006,
            "window": [
              0.020001589,
              300.119984264
            ],
            "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": 0.2,
            "unit": "s",
            "n": 14996,
            "window": [
              0.020001589,
              300.119984264
            ],
            "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": 0.018557367077209477,
            "unit": "",
            "n": 14996,
            "window": [
              0.020001589,
              300.119984264
            ],
            "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": 15006,
            "window": [
              0.020001589,
              300.119984264
            ],
            "note": "",
            "validity": "valid",
            "reason_code": ""
          },
          "regime_comparison_possible": {
            "key": "regime_comparison_possible",
            "label": "Gyro-quiet vs gyro-active comparison possible",
            "value": false,
            "unit": "",
            "n": 14974,
            "window": "whole run",
            "note": "2 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": 0.3532141,
            "unit": "rad/s",
            "n": 14974,
            "window": "whole run",
            "note": "threshold 0.02 rad/s",
            "validity": "valid",
            "reason_code": ""
          }
        },
        "caveats": [
          "Regime framing skipped: the run has 2 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 0.35321 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": [
          300.206,
          300.206
        ],
        "validity": "valid",
        "reason_code": "",
        "note": ""
      },
      "temperature_range_c": {
        "value": 1.0,
        "unit": "\u00b0C",
        "n": 31,
        "window": [
          0.0,
          300.206
        ],
        "validity": "valid",
        "reason_code": "",
        "note": ""
      },
      "temperature_slope_c_per_min": {
        "value": -0.15714526662869602,
        "unit": "\u00b0C/min",
        "n": 31,
        "window": [
          0.0,
          300.206
        ],
        "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": 360.303,
        "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": "224c2717-7885-4771-b7e1-9c6e2bc52990",
      "day_utc": "20260821",
      "rows_day": 2792,
      "rows_context": 69,
      "ambient_control_windows": 85,
      "ambient_delta_mean_nt": -1050.11,
      "ambient_delta_median_nt": -5.43,
      "ambient_windows_more_positive_fraction": 0.082,
      "window_utc_ms": [
        1787347433728,
        1787348334031
      ],
      "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": 112.868785546511,
      "denominator_floor_nt": 1.0,
      "rows": 843,
      "valid_rows": 753,
      "top_candidate_windows": [
        {
          "window_start_s": 201.0,
          "window_end_s": 211.0,
          "window_length_s": 10,
          "n": 501,
          "raw_score": 5.3378462144288275,
          "score": 5.3378462144288275,
          "valid": true,
          "invalid_reasons": "",
          "signed_change_nt": 602.4762196566229,
          "absolute_change_nt": 602.4762196566229,
          "motion_fraction": 0.0,
          "artifact_fraction": 0.0,
          "normalization_denominator_nt": 112.868785546511
        },
        {
          "window_start_s": 202.0,
          "window_end_s": 212.0,
          "window_length_s": 10,
          "n": 499,
          "raw_score": 5.310608977295065,
          "score": 5.310608977295065,
          "valid": true,
          "invalid_reasons": "",
          "signed_change_nt": 599.4019857796928,
          "absolute_change_nt": 599.4019857796928,
          "motion_fraction": 0.0,
          "artifact_fraction": 0.0,
          "normalization_denominator_nt": 112.868785546511
        },
        {
          "window_start_s": 203.0,
          "window_end_s": 213.0,
          "window_length_s": 10,
          "n": 501,
          "raw_score": 5.2364653722454175,
          "score": 5.2364653722454175,
          "valid": true,
          "invalid_reasons": "",
          "signed_change_nt": 591.033487121699,
          "absolute_change_nt": 591.033487121699,
          "motion_fraction": 0.0,
          "artifact_fraction": 0.0,
          "normalization_denominator_nt": 112.868785546511
        },
        {
          "window_start_s": 204.0,
          "window_end_s": 214.0,
          "window_length_s": 10,
          "n": 500,
          "raw_score": 5.163932004139904,
          "score": 5.163932004139904,
          "valid": true,
          "invalid_reasons": "",
          "signed_change_nt": 582.8467339520316,
          "absolute_change_nt": 582.8467339520316,
          "motion_fraction": 0.0,
          "artifact_fraction": 0.0,
          "normalization_denominator_nt": 112.868785546511
        },
        {
          "window_start_s": 201.0,
          "window_end_s": 221.0,
          "window_length_s": 20,
          "n": 1000,
          "raw_score": 5.127396668174008,
          "score": 5.127396668174008,
          "valid": true,
          "invalid_reasons": "",
          "signed_change_nt": 578.7230349520271,
          "absolute_change_nt": 578.7230349520271,
          "motion_fraction": 0.0,
          "artifact_fraction": 0.0,
          "normalization_denominator_nt": 112.868785546511
        },
        {
          "window_start_s": 205.0,
          "window_end_s": 215.0,
          "window_length_s": 10,
          "n": 500,
          "raw_score": 5.0987645978957685,
          "score": 5.0987645978957685,
          "valid": true,
          "invalid_reasons": "",
          "signed_change_nt": 575.4913679520399,
          "absolute_change_nt": 575.4913679520399,
          "motion_fraction": 0.0,
          "artifact_fraction": 0.0,
          "normalization_denominator_nt": 112.868785546511
        },
        {
          "window_start_s": 202.0,
          "window_end_s": 222.0,
          "window_length_s": 20,
          "n": 999,
          "raw_score": 5.056528714930143,
          "score": 5.056528714930143,
          "valid": true,
          "invalid_reasons": "",
          "signed_change_nt": 570.7242551352251,
          "absolute_change_nt": 570.7242551352251,
          "motion_fraction": 0.0,
          "artifact_fraction": 0.0,
          "normalization_denominator_nt": 112.868785546511
        },
        {
          "window_start_s": 206.0,
          "window_end_s": 216.0,
          "window_length_s": 10,
          "n": 500,
          "raw_score": 5.000458888781632,
          "score": 5.000458888781632,
          "valid": true,
          "invalid_reasons": "",
          "signed_change_nt": 564.3957219520388,
          "absolute_change_nt": 564.3957219520388,
          "motion_fraction": 0.0,
          "artifact_fraction": 0.0,
          "normalization_denominator_nt": 112.868785546511
        },
        {
          "window_start_s": 207.0,
          "window_end_s": 217.0,
          "window_length_s": 10,
          "n": 500,
          "raw_score": 4.960233808144732,
          "score": 4.960233808144732,
          "valid": true,
          "invalid_reasons": "",
          "signed_change_nt": 559.8555659520414,
          "absolute_change_nt": 559.8555659520414,
          "motion_fraction": 0.0,
          "artifact_fraction": 0.0,
          "normalization_denominator_nt": 112.868785546511
        },
        {
          "window_start_s": 209.0,
          "window_end_s": 219.0,
          "window_length_s": 10,
          "n": 500,
          "raw_score": 4.945052640103366,
          "score": 4.945052640103366,
          "valid": true,
          "invalid_reasons": "",
          "signed_change_nt": 558.1420859520349,
          "absolute_change_nt": 558.1420859520349,
          "motion_fraction": 0.0,
          "artifact_fraction": 0.0,
          "normalization_denominator_nt": 112.868785546511
        }
      ],
      "note": "Scores use feedback_meter level/drift_sigma. Both signs are treated symmetrically; ranked windows are descriptive."
    }
  }
}