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Systematic discovery & rigorous validation of statistical anomalies in open HF market data (hfmarketdata.io) — pre-registered, artifact-null-driven, fully reproducible. Live atlas: www.anomaly-atlas.io

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1# =============================================================================2#  Project   : anomaly-atlas3#  File      : experiments/candidate_03/benchmark.py4#  Purpose   : Benchmark runner: Candidate 03 (selected in Phase 4 from research/candidate_rankin…5#  Author    : Simon-Pierre Boucher6#  Contact   : contact@spboucher.ai7#  Data src  : hfmarketdata.io (sole data source)8#  Created   : 2026-08-129#  Modified  : 2026-08-1210#  Platform  : macOS / Apple Silicon (arm64)11#  License   : All rights reserved (research code)12# =============================================================================1314"""Benchmark entry point for candidate_03.1516Must embed the hardware manifest in all result output17(see benchmarks/hardware_manifest.py) and write results to18results/candidate_03/<timestamp>/. Uses hfmarketdata.io data ONLY, exclusively19through src/anomaly_atlas/data/hf_client.py.20"""2122import sys23from pathlib import Path2425sys.path.insert(0, str(Path(__file__).resolve().parents[2] / "benchmarks"))26from hardware_manifest import collect_manifest  # noqa: E402272829def main() -> None:30    collect_manifest()  # embedded in results once implemented31    raise NotImplementedError("experiment not yet implemented")323334if __name__ == "__main__":35    main()36