{
  "paper_id": "ATT-0594",
  "paper_title": "ChronosX: Adapting Pretrained Time Series Models with Exogenous Variables",
  "validation_status": "PASS_WITH_CONDITIONAL_USE_LIMITS_AND_REVIEW_ERRATA",
  "mechanical_status": "PASS_EFFECTIVE_AFTER_ERRATA",
  "original_mechanical_status": "FAIL",
  "frozen_reviewers": 5,
  "effective_reviewers": 5,
  "legacy_votes": 0,
  "minimum_body_hanzi": 1463,
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    "B": 1463,
    "C": 1611,
    "D": 1554,
    "E": 1674
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  "numeric_votes": 100,
  "all_dimension_slots": 120,
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  "unknown_dimensions": [
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    "F3",
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  "tentative_numeric_vote_share": 0.2,
  "observed_equal_weight_mean": 73.4,
  "mean_is_provisional_sorting_aid": true,
  "original_mean": 73.4,
  "statistics_method": "Per dimension mean and population variance (ddof=0) use numeric reviewer votes only. Unknown/NA are not imputed. An accepted erratum replaces its own same reviewer vote; it is not an additional vote.",
  "effective_statistics_path": "/workspace/shared/candidate_review_batch001/validation/ATT-0594/statistics_effective.json",
  "frozen_original_statistics_path": "/workspace/shared/candidate_review_batch001/validation/ATT-0594/statistics_frozen_original.json",
  "source_audit_path": "/workspace/shared/candidate_review_batch001/validation/ATT-0594/source_audit.json",
  "accepted_errata": [
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      "path": "/workspace/shared/candidate_review_batch001/reviewer_b/ATT-0594/ERRATUM_B_SCOPE_001.json",
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      "scores_changed": false
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      "reviewer": "C",
      "path": "/workspace/shared/candidate_review_batch001/reviewer_c/ATT-0594_C_signed_addendum.v1.json",
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      "companion_sha256": {
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      "same_vote_not_additional_reviewer": true,
      "scores_changed": false
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    {
      "reviewer": "D",
      "path": "/workspace/shared/candidate_review_batch001/reviewer_d/ATT-0594_CORRECTION_01.json",
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      "scores_changed": false
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  "read_before_history_verification": "Explicitly attested by reviewers; full historical review unavailable; not independently timed.",
  "risk_banner": "Future covariate availability, unequal tuning budgets, and missing seed uncertainty limit deployment and close-ranking claims. No demonstrated leakage or critical method failure was found."
}