{
 "schema_version": "bci-report-foundation-checkpoints-update-v1",
 "release_id": "foundation-checkpoints-update-20261106",
 "generated_at": "2026-11-06",
 "status": "reviewed aggregate",
 "title": "LaBraM at Scale and REVE Small as frozen probes on the core protocols",
 "placement": {
  "topic": "/topics/does-pretraining-help/",
  "topic_anchor": "more-checkpoints",
  "step_anchor": "fc-quark-g-step",
  "protocol_anchor": "more-checkpoints",
  "protocol_pages": [
   "/protocols/mi-rest/",
   "/protocols/idle/",
   "/protocols/beta-8ch/",
   "/protocols/beta-4ch/",
   "/protocols/arithmetic-rest/",
   "/protocols/p300-target/",
   "/protocols/semantic-target/",
   "/protocols/sleep-scalp/"
  ],
  "methods": [
   {
    "page": "/methods/labram/",
    "anchor": "labram-at-scale"
   },
   {
    "page": "/methods/reve/",
    "anchor": "reve-small"
   }
  ],
  "data_use": {
   "page": "/data-use/",
   "anchor": "sources-foundation-checkpoints"
  },
  "matrix": false,
  "leaderboard": false
 },
 "metric_units": "balanced accuracy and macro F1 are equal-person means of per-person values, proportions in [0, 1]; each percent block gives the same figures × 100, rounded to 12 decimals; paired differences and their intervals are proportions, printed in percentage points; idle trial counts are whole trials out of 60; the mean window AUROC is a proportion",
 "design": {
  "frozen_probe": "The published 250 Hz microvolt windows, resampled from 250 to 200 Hz (resample_poly 4, 5); 1 s and 2 s windows are one or two patches; sleep is the mean of the pooled features of 15 two-second segments; recorded channels only, with no padding or interpolation.",
  "head": "Ridge, α = 100 (Cholesky), on train-fold-standardised features, class-balanced except on BETA; idle: a per-person logistic head with a calibration-only threshold and a trigger after two consecutive decisions.",
  "folds": "Participant-held-out: 5 folds, 7 on BETA.",
  "intervals": "Cells: a descriptive participant bootstrap of the equal-person mean, 10,000 draws. Paired differences: a paired participant bootstrap, 10,000 draws, one draw matrix per dataset, with BETA's two montages resampled jointly.",
  "determinism": "Extraction and heads are deterministic: each cell has one value.",
  "backend": "The cells of Quark-B, Quark-L, Quark-H, Atom-L, Molecule-L and REVE Small ran on Local Ubuntu / CPU with 4 threads; Quark-G and the Quark-H baseline of its step ran on Local Ubuntu / CUDA."
 },
 "protocols": [
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   "title": "Motor imagery & rest",
   "dataset": "ds003810",
   "type": "accuracy",
   "people": 10,
   "windows": 1200,
   "chance_level": 0.5
  },
  {
   "id": "idle",
   "title": "Idle & command",
   "dataset": "ds005342",
   "type": "tradeoff",
   "people": 4,
   "windows": 1440
  },
  {
   "id": "beta-8ch",
   "title": "SSVEP · 8 channels",
   "dataset": "BETA",
   "type": "accuracy",
   "people": 70,
   "windows": 11200,
   "chance_level": 0.025
  },
  {
   "id": "beta-4ch",
   "title": "SSVEP · 4 channels",
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   "type": "accuracy",
   "people": 70,
   "windows": 11200,
   "chance_level": 0.025
  },
  {
   "id": "arithmetic-rest",
   "title": "Arithmetic & rest",
   "dataset": "EEGMAT",
   "type": "accuracy",
   "people": 36,
   "windows": 2160,
   "chance_level": 0.5
  },
  {
   "id": "p300-target",
   "title": "P300 target ERP",
   "dataset": "ds006593",
   "type": "accuracy",
   "people": 21,
   "windows": 2520,
   "chance_level": 0.5
  },
  {
   "id": "semantic-target",
   "title": "Semantic target ERP",
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   "type": "accuracy",
   "people": 30,
   "windows": 3600,
   "chance_level": 0.5
  },
  {
   "id": "sleep-scalp",
   "title": "Sleep staging",
   "dataset": "EESM19",
   "type": "accuracy",
   "people": 20,
   "windows": 3000,
   "chance_level": 0.2
  }
 ],
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     "interval_95": [
      22.803571428571,
      31.089285714286
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     "chance_level": 2.5
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    "exposure": {
     "status": "not_exposed",
     "flag": null,
     "statement": "outside the Quark collection's pretraining list (data_manifests/pretraining/datasets.csv at faa387d9)"
    }
   },
   {
    "model": "quark-giant",
    "protocol": "arithmetic-rest",
    "status": "complete",
    "backend": "Local Ubuntu / CUDA",
    "people": 36,
    "windows": 2160,
    "feature_width": 1600,
    "balanced_accuracy": 0.5935185185185184,
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     "chance_level": 50.0
    },
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     "status": "not_exposed",
     "flag": null,
     "statement": "outside the Quark collection's pretraining list (data_manifests/pretraining/datasets.csv at faa387d9)"
    }
   },
   {
    "model": "quark-giant",
    "protocol": "p300-target",
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    "people": 21,
    "windows": 2520,
    "feature_width": 1600,
    "balanced_accuracy": 0.5031746031746032,
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     "chance_level": 50.0
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     "status": "not_exposed",
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     "statement": "outside the Quark collection's pretraining list (data_manifests/pretraining/datasets.csv at faa387d9)"
    }
   },
   {
    "model": "quark-giant",
    "protocol": "semantic-target",
    "status": "complete",
    "backend": "Local Ubuntu / CUDA",
    "people": 30,
    "windows": 3600,
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    "balanced_accuracy": 0.5175,
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    "percent": {
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      53.444444444444
     ],
     "chance_level": 50.0
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     "status": "not_exposed",
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     "statement": "outside the Quark collection's pretraining list (data_manifests/pretraining/datasets.csv at faa387d9)"
    }
   },
   {
    "model": "quark-giant",
    "protocol": "sleep-scalp",
    "status": "complete",
    "backend": "Local Ubuntu / CUDA",
    "people": 20,
    "windows": 3000,
    "feature_width": 1600,
    "balanced_accuracy": 0.6726666666666665,
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    "percent": {
     "balanced_accuracy": 67.266666666667,
     "interval_95": [
      65.6,
      68.866666666667
     ],
     "chance_level": 20.0
    },
    "exposure": {
     "status": "not_exposed",
     "flag": null,
     "statement": "outside the Quark collection's pretraining list (data_manifests/pretraining/datasets.csv at faa387d9)"
    }
   }
  ],
  "per_protocol": [
   {
    "id": "C4",
    "a": "quark-giant",
    "b": "quark-huge",
    "b_note": "re-run on the same GPU",
    "protocol": "mi-rest",
    "dataset": "ds003810",
    "difference": -0.01499999999999998,
    "interval_95": [
     -0.03916666666666664,
     0.015833333333333366
    ],
    "excludes_zero": false,
    "cohort_size": 10
   },
   {
    "id": "C4",
    "a": "quark-giant",
    "b": "quark-huge",
    "b_note": "re-run on the same GPU",
    "protocol": "beta-8ch",
    "dataset": "BETA",
    "difference": 0.013125,
    "interval_95": [
     0.003392857142857141,
     0.02348214285714285
    ],
    "excludes_zero": true,
    "cohort_size": 70
   },
   {
    "id": "C4",
    "a": "quark-giant",
    "b": "quark-huge",
    "b_note": "re-run on the same GPU",
    "protocol": "beta-4ch",
    "dataset": "BETA",
    "difference": 0.006071428571428572,
    "interval_95": [
     -0.003752232142857143,
     0.01571651785714283
    ],
    "excludes_zero": false,
    "cohort_size": 70
   },
   {
    "id": "C4",
    "a": "quark-giant",
    "b": "quark-huge",
    "b_note": "re-run on the same GPU",
    "protocol": "arithmetic-rest",
    "dataset": "EEGMAT",
    "difference": -0.051388888888888914,
    "interval_95": [
     -0.08842592592592594,
     -0.014351851851851866
    ],
    "excludes_zero": true,
    "cohort_size": 36
   },
   {
    "id": "C4",
    "a": "quark-giant",
    "b": "quark-huge",
    "b_note": "re-run on the same GPU",
    "protocol": "p300-target",
    "dataset": "ds006593",
    "difference": -0.02261904761904764,
    "interval_95": [
     -0.046825396825396826,
     0.0007936507936507802
    ],
    "excludes_zero": false,
    "cohort_size": 21
   },
   {
    "id": "C4",
    "a": "quark-giant",
    "b": "quark-huge",
    "b_note": "re-run on the same GPU",
    "protocol": "semantic-target",
    "dataset": "ds005383",
    "difference": -0.004444444444444436,
    "interval_95": [
     -0.028611111111111094,
     0.019444444444444445
    ],
    "excludes_zero": false,
    "cohort_size": 30
   },
   {
    "id": "C4",
    "a": "quark-giant",
    "b": "quark-huge",
    "b_note": "re-run on the same GPU",
    "protocol": "sleep-scalp",
    "dataset": "EESM19",
    "difference": -0.056000000000000015,
    "interval_95": [
     -0.06866666666666667,
     -0.041999999999999996
    ],
    "excludes_zero": true,
    "cohort_size": 20
   }
  ],
  "step": {
   "id": "C4-avg",
   "averaging": "dataset-weighted",
   "weights": {
    "mi-rest": 0.16666666666666666,
    "beta-8ch": 0.08333333333333333,
    "beta-4ch": 0.08333333333333333,
    "arithmetic-rest": 0.16666666666666666,
    "p300-target": 0.16666666666666666,
    "semantic-target": 0.16666666666666666,
    "sleep-scalp": 0.16666666666666666
   },
   "difference": -0.023309027777777783,
   "interval_95": [
    -0.033026003086419765,
    -0.013180454971340398
   ],
   "excludes_zero": true
  },
  "multiplicity": {
   "intervals": 7,
   "expected_excluding_zero_by_chance": 0.35,
   "excluding_zero": 3
  },
  "device_note": {
   "beta4ch_step": 0.006071428571428572,
   "beta4ch_against_displayed": 0.005982142857142769
  },
  "methods_clause": {
   "gpu_path": "On the GPU path, one published cell (LaBraM, arithmetic and rest) was re-extracted and matched its published value.",
   "quark_h_rerun": "The GPU re-run of Quark-H, the baseline of the Quark-G step, reproduces the Quark-H cells shown except two window predictions on beta-4ch."
  },
  "templates": {
   "T-LADDER-H3": "The Quark ladder: B, L, H and G",
   "T-READ": "Under this probe, among Quark-B, Quark-L and Quark-H, the larger released encoders did not reach a higher average balanced accuracy on these protocols.",
   "T-C4AVG": "Quark-G minus Quark-H, with both encoders run on the same GPU, averaged {c4} over the six datasets, dataset-weighted (95% interval {lo} to {hi}); the probe's input width doubles from 800 to 1600 under one fixed penalty, so this step includes that change.",
   "T-W": "One fixed ridge probe (α = 100 on standardised training-fold features) reads every encoder; the feature width grows from 200 to 400 to 800 to 1600, so each step, the Quark-G step included, includes the probe's width under one penalty.",
   "T-REL": "Each Quark size, Quark-G included, comes with its own pretraining recipe; the ladder compares the encoders as released.",
   "T-AVG": "Each of the six datasets weighs one sixth; the two BETA montages, the same 70 people, one twelfth each. The values are balanced-accuracy points across 2-, 5- and 40-class protocols, not normalised effects. The intervals resample people within these datasets, not the choice of datasets, and the three step summaries, prespecified in two protocols, carry no multiplicity correction.",
   "T-C4CAP": "Quark-G minus Quark-H, both on the same GPU: paired participant bootstrap, 10,000 draws; the probe's input width doubles from 800 to 1600 under one fixed penalty.",
   "T-C4PP": "Per protocol, Quark-G was lower than Quark-H on {lower_list} and higher on {higher_list}, each step including the probe's input width doubling from 800 to 1600 under one fixed penalty; the other {k} intervals include zero. If no true difference existed, about {expected} of the {intervals} intervals would exclude zero by chance; {top_two} carry most of the average, and the two BETA montages are the same people.",
   "T-DEV": "Quark-G and the Quark-H baseline of its step ran on Local Ubuntu / CUDA; the Quark-H cells shown ran on Local Ubuntu / CPU. The GPU re-run reproduces them except two window predictions on beta-4ch, where the step reads {b4step} against the GPU baseline ({b4disp} against the cell shown) and, like every Quark-G step, includes the probe's input width doubling from 800 to 1600 under one fixed penalty.",
   "T-DEV-SHORT": "Run on Local Ubuntu / CUDA; its step is read against a GPU re-run of Quark-H and includes the probe's input width doubling from 800 to 1600 under one fixed penalty (see the topic page).",
   "T-METH": "On the GPU path, one published cell (LaBraM, arithmetic and rest) was re-extracted and matched its published value.",
   "T-R4": "Quark-G minus Quark-H, with both encoders on the same GPU: {c4} averaged over six datasets, dataset-weighted (95% interval {lo} to {hi}); the probe's input width doubles from 800 to 1600 under one fixed penalty, so the step includes that change."
  },
  "slots": {
   "c4": "quark_giant.step.difference",
   "lo": "quark_giant.step.interval_95.0",
   "hi": "quark_giant.step.interval_95.1",
   "b4step": "quark_giant.device_note.beta4ch_step",
   "b4disp": "quark_giant.device_note.beta4ch_against_displayed",
   "expected": "quark_giant.multiplicity.expected_excluding_zero_by_chance",
   "intervals": "quark_giant.multiplicity.intervals",
   "lower_list": "quark_giant.per_protocol",
   "higher_list": "quark_giant.per_protocol",
   "k": "quark_giant.per_protocol",
   "top_two": "quark_giant.per_protocol"
  },
  "publication_decision": {
   "ids": [
    "D54",
    "D60"
   ]
  },
  "records_sha256": {
   "protocol": "012b6040b82338636a6be152ea6593329e4824dee6a1fb92fbb0f2708f47d2e1",
   "amendments": "39b1127c3e73b517a9a5650bc4b48fac08e4cab8e14e8bbda29702650ba261f2",
   "freeze": "63c1561a835d1a079fad56249ca5c2fc092983de01feea080230c71cbd55de35",
   "inputs": "d3bf687d2ef0a86aecb4918b2768386a1837155c127ca775d9e814b9a2a660f0",
   "smoke_test": "3a6c31e5309e728d5a813d6a77f795862f0618ae5df9a0fe5975d2fa262299ac",
   "smoke_test_a1": "27ab318f477ee22b814c5cfe82422b19e8667bb4bfc4a0e4af1a5e2c24cc741a",
   "audit_brief_n1": "c2fecd3e48fd54bcf0d62b55a01c9879cba32b3911f64efd5a049cfa5446063a",
   "aggregate": "c6b2e91bd5433e9851ed17f11e52dc29e92b7e84e307a20dba73323f832f7ae1",
   "seal": "7f8d1212186b67ce69ce3d83945e1493d93142c1be7563eaa1b52d54348b2f89",
   "run_log": "47e3e23e7163a82a39bbbb54e1aeb5b3bec4f2ca9ddb0bc01e194d6f2dfbadc5",
   "run_receipt": "cfdef6ea6e94c2f63f6ce1e35c1c94a8e1ee2dcb61a0dcd931e477c942b3a1e4",
   "pre_execution_review": "291c8fdfc33d52ebf5ced414f1a9571eb6b91d0e57afd3cf6249bd172f755776",
   "audit": "76138a4c2e398e3320e8234638ec569bd36179cd7c9a02bab68c68c5810c3ac9",
   "interpretation_review": "4e668d52ce0d08fbd173de86554e206003a8da11139ec2344029352f6b8744c0",
   "handoff": "5da49036344d18003b51e2de881a11699698cc2de1e9d0c74c760d791c58929d"
  }
 },
 "exposure": {
  "checked_on": {
   "labram_at_scale": "2026-11-05",
   "reve": "2026-10-04"
  },
  "source": {
   "file": "data_manifests/pretraining/datasets.csv",
   "repository": "AlbertMentat/LaBraM-at-Scale",
   "revision": "faa387d9",
   "paper_table": "Table 5"
  },
  "flag_text": "its pretraining corpus includes this protocol's dataset",
  "flagged": [
   {
    "model": "atom-large",
    "protocol": "mi-rest"
   },
   {
    "model": "atom-large",
    "protocol": "idle"
   },
   {
    "model": "atom-large",
    "protocol": "arithmetic-rest"
   },
   {
    "model": "atom-large",
    "protocol": "p300-target"
   },
   {
    "model": "atom-large",
    "protocol": "semantic-target"
   },
   {
    "model": "molecule-large",
    "protocol": "mi-rest"
   },
   {
    "model": "molecule-large",
    "protocol": "idle"
   },
   {
    "model": "molecule-large",
    "protocol": "arithmetic-rest"
   },
   {
    "model": "molecule-large",
    "protocol": "p300-target"
   },
   {
    "model": "molecule-large",
    "protocol": "semantic-target"
   }
  ],
  "quark_sources": [
   "Alljoined",
   "Game",
   "HMC",
   "SEED",
   "SEED-IV",
   "SEED-V",
   "SEED-VII",
   "THINGS-EEG2",
   "TUH"
  ],
  "reve_small": {
   "status": "not_exposed_inferred",
   "statement": "its card does not restate its corpus; the REVE corpus list (checked 2026-10-04) includes none of the core datasets"
  }
 },
 "methods_note": {
  "reextraction": [
   {
    "published_cell": "REVE Base, arithmetic and rest",
    "result": "matched"
   },
   {
    "published_cell": "LaBraM, arithmetic and rest",
    "result": "matched"
   }
  ],
  "adapter_check": "The audit re-extracted sample windows of two LaBraM at Scale encoders, Quark-B and Molecule-L, with its own code and matched them.",
  "reve_small_check": "An export-stage check re-extracted sample windows of REVE Small on CPU and matched them.",
  "gpu_check": "On the GPU path, one published cell (LaBraM, arithmetic and rest) was re-extracted and matched its published value."
 },
 "rights": {
  "labram_at_scale": {
   "code": "MIT",
   "weights": "MIT",
   "licence_sha256": "d5a942b3c81cd683fbf6a3ad41576fa5a946811954a0b2f6edc7d44ff942a5e7",
   "access": "ungated",
   "code_repository": "AlbertMentat/LaBraM-at-Scale @ faa387d9",
   "weights_repository": "Pan-Junyu/LaBraM-at-Scale @ a0b0ce27",
   "paper": "https://arxiv.org/abs/2611.03165",
   "citation": "Pan J-Y, Yin R, Lu B-L, Li D, Zheng W-L, Wang Y. LaBraM at Scale: Scaling Data and Models for EEG Pretraining. arXiv 2611.03165, 2026.",
   "cite_also": "https://arxiv.org/abs/2405.18765",
   "naming": "collection, size and revision"
  },
  "reve_small": {
   "licence": "REVE Responsible Use License v1.0",
   "licence_sha256": "cda77c38a1fcf002009678642608748f221458f83bc5ee3944f1e0c83939cd96",
   "version": "reve-small @ 3565bdcb",
   "paper": "https://arxiv.org/abs/2510.21585",
   "conditions": [
    "aggregate scientific results only",
    "no re-identification, inversion, membership inference or profiling",
    "cite the REVE paper and name the model version",
    "no adapted weights"
   ],
   "approval": "owner decision D37"
  },
  "datasets": [
   {
    "protocol": "mi-rest",
    "dataset": "ds003810",
    "licence": "CC0-1.0"
   },
   {
    "protocol": "idle",
    "dataset": "ds005342",
    "licence": "CC0-1.0"
   },
   {
    "protocol": "beta-8ch",
    "dataset": "BETA",
    "licence": "CC BY 4.0"
   },
   {
    "protocol": "beta-4ch",
    "dataset": "BETA",
    "licence": "CC BY 4.0"
   },
   {
    "protocol": "arithmetic-rest",
    "dataset": "EEGMAT",
    "licence": "ODC-By 1.0"
   },
   {
    "protocol": "p300-target",
    "dataset": "ds006593",
    "licence": "CC0-1.0"
   },
   {
    "protocol": "semantic-target",
    "dataset": "ds005383",
    "licence": "CC BY 4.0, the stricter of the two stated terms"
   },
   {
    "protocol": "sleep-scalp",
    "dataset": "EESM19",
    "licence": "CC0-1.0"
   }
  ],
  "weights_distributed": false
 },
 "release_record": {
  "date": "2026-11-06",
  "decision": "Publish the frozen-probe cells of six LaBraM at Scale encoders (Quark-B, Quark-L, Quark-H and Quark-G, and the Large encoders of Atom and Molecule) and of REVE Small, the Quark ladder's paired differences and the Quark-G step beside the core matrix, as aggregates only (owner decisions D37, D45, D46, D47, D54, D58 and D60).",
  "rights": "LaBraM at Scale code and weights are MIT and ungated; REVE Small is under the REVE Responsible Use License v1.0, aggregate scientific results only; no weights are distributed."
 },
 "required_limitations": [
  {
   "id": "probe-width",
   "text": "One fixed ridge probe (α = 100 on standardised training-fold features) reads every encoder; the feature width grows from 200 to 400 to 800 to 1600, so each step, the Quark-G step included, includes the probe's width under one penalty."
  },
  {
   "id": "released-encoders",
   "text": "Each Quark size, Quark-G included, comes with its own pretraining recipe; the ladder compares the encoders as released."
  },
  {
   "id": "averages",
   "text": "Each of the six datasets weighs one sixth; the two BETA montages, the same 70 people, one twelfth each. The values are balanced-accuracy points across 2-, 5- and 40-class protocols, not normalised effects. The intervals resample people within these datasets, not the choice of datasets, and the three step summaries, prespecified in two protocols, carry no multiplicity correction."
  },
  {
   "id": "per-protocol",
   "text": "If no true difference existed, about one in twenty of the per-protocol intervals would exclude zero by chance; the near-zero average of Quark-H minus Quark-L is made of differences in both directions, and the two BETA montages are the same people."
  },
  {
   "id": "exposure",
   "text": "The Large encoders of LaBraM at Scale's Atom and Molecule collections are read the same way. Their pretraining lists include five of the core datasets, so their cells on motor imagery and rest, idle, arithmetic and rest, P300 target and semantic target carry the flag \"its pretraining corpus includes this protocol's dataset\". Atom and Molecule differ from Quark in corpus size, composition and input normalisation, so these rows stand on their own."
  },
  {
   "id": "reve-small-label",
   "text": "REVE Small's encoder was released at epoch 15 of a 200-epoch schedule; every REVE Small value carries the label \"early checkpoint (epoch 15 of 200)\"."
  },
  {
   "id": "reve-small-exposure",
   "text": "REVE Small's card does not restate its corpus; its exposure is read from the REVE corpus list (checked 2026-10-04), which includes none of the core datasets."
  },
  {
   "id": "reve-small-input",
   "text": "REVE Small reads its input as the REVE Base and Large rows do: each segment's per-channel mean is removed before dividing by 100; no sensitivity run was made for Small."
  },
  {
   "id": "idle-pooling",
   "text": "LaBraM at Scale's pooled features are global on idle; the published LaBraM idle row kept the channel axis."
  },
  {
   "id": "idle-trials",
   "text": "Idle is a within-person protocol: each row gives the cohort size, trial counts and window metrics, with no contrast."
  }
 ],
 "audits": {
  "numeric": {
   "passed": 38,
   "of": 38
  },
  "quark_giant_numeric": {
   "passed": 41,
   "of": 41
  },
  "export": {
   "file": "foundation-checkpoints-export-audit.json"
  }
 },
 "not_published": [
  "Per-person, per-fold and per-window values of any kind; features, fitted heads, idle thresholds and participant identifiers.",
  "Counts of people meeting a criterion on the idle protocol, whose cohort of four prints as a protocol fact beside the trial counts.",
  "Contrasts that were not computed: Atom-L or Molecule-L against Quark, REVE Small against REVE Base or Large, and an average of Quark-H minus Quark-B.",
  "Quark-G against Quark-B or Quark-L, any sum of ladder steps, and a GPU restatement of the Quark-L and Quark-H steps, with anything derived from them.",
  "The GPU re-run of Quark-H as cells: it is the baseline of the Quark-G step, and the Quark-H cells shown are the CPU cells.",
  "The re-extraction and attention-kernel checks as results; they are a methods note.",
  "Context values of the numeric checks: an unweighted mean over protocols, intervals from an unrelated bootstrap seed, a numeric order of the BETA participants and training-fold sizes.",
  "Weights of any kind: none were adapted, and downloaded weights are never redistributed.",
  "Timings, memory, device readings, free-space values, the compute estimate and the download time from the runs.",
  "The research records themselves, pinned by hash in the release manifest because several carry private storage paths."
 ],
 "rounding": {
  "rule": "exact value rounded half away from zero at the printed precision",
  "helper_sha256": "1aaf37e466d56c55d5737233f6f989276119e4f9da351110251bb026cb8f4c9b",
  "ties": [
   {
    "path": "cells.30.percent.balanced_accuracy",
    "value": 52.75,
    "fmt": "pct1raw",
    "prints": "52.8%"
   },
   {
    "path": "cells.30.percent.interval_95.0",
    "value": 51.25,
    "fmt": "pct1raw",
    "prints": "51.3%"
   },
   {
    "path": "cells.40.percent.interval_95.0",
    "value": 58.25,
    "fmt": "pct1raw",
    "prints": "58.3%"
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