{
  "schema": "chematic.io.public-wheel-feature-benchmark.v1",
  "checked_at": "2026-10-14T13:02:48.837232+00:00",
  "source_review": {
    "tag": "v1.1.4",
    "commit": "cac480fb23cd8adeec6e5e9bed1f18677f87b392",
    "release_published_at": "2026-10-14T11:53:19Z",
    "publication_workflow": "https://github.com/kent-tokyo/chematic/actions/runs/38559674509",
    "published_wheel_chemistry_gate": "https://github.com/kent-tokyo/chematic/actions/runs/38562931659"
  },
  "packages": [
    {
      "name": "chematic",
      "version": "1.1.3",
      "filename": "chematic-1.1.3-cp313-cp313-macosx_11_0_arm64.whl",
      "sha256": "5569b170b037108d13e9af51386173050ac3b4ac4c798bf706d2a522ddd0e17b",
      "url": "https://files.pythonhosted.org/packages/74/1d/d0ab1f59703585be2adcb627c2467d64a8d9177da6183f6904571eabb02b/chematic-1.1.3-cp313-cp313-macosx_11_0_arm64.whl",
      "installed_native_files_verified": 1
    },
    {
      "name": "chematic",
      "version": "1.1.4",
      "filename": "chematic-1.1.4-cp313-cp313-macosx_11_0_arm64.whl",
      "sha256": "581cb2f45edb8743d8dfd59298e59ac62d60f64af1d2050b29e85431d90003c0",
      "url": "https://files.pythonhosted.org/packages/3e/fa/e3e6d20a8e20096459d20b17d20d9a461b4d20ec4e2be714ce00550a9848/chematic-1.1.4-cp313-cp313-macosx_11_0_arm64.whl",
      "installed_native_files_verified": 1
    },
    {
      "name": "rdkit",
      "version": "2026.9.1",
      "filename": "rdkit-2026.9.1-cp313-cp313-macosx_11_0_arm64.whl",
      "sha256": "29b6176ace255989abde23d40d2187b5ed5effdb2f00dadaced24f181ab27046",
      "url": "https://files.pythonhosted.org/packages/29/53/4277a2f4708e0c0a61917cf7075cc66ccfc66acb21c8ce043612a5850a56/rdkit-2026.9.1-cp313-cp313-macosx_11_0_arm64.whl",
      "installed_native_files_verified": 63
    }
  ],
  "environment": {
    "platform": "macOS-27.0.1-arm64-arm-64bit-Mach-O",
    "python": "3.13.6",
    "numpy": "2.5.4",
    "measurement_lane": "Published macOS arm64 CPython 3.13 wheels; sequential single-process calls"
  },
  "corpus": {
    "url": "https://raw.githubusercontent.com/kent-tokyo/chematic/cac480fb23cd8adeec6e5e9bed1f18677f87b392/validation/benchmark_corpora/rdkit-js-browser-10k-v1.smi",
    "sha256": "f48777e96f74738336f47f682fbff5af6775a3474fe25daa28b595340feee95f",
    "slices": [
      {
        "offset": 0,
        "rows": 1000
      },
      {
        "offset": 5000,
        "rows": 1000
      }
    ],
    "selection": "Fixed public development corpus slices, selected before this article run; all rows retained"
  },
  "protocol": {
    "blocks": 21,
    "repeats_per_block": 5,
    "engine_order": "Three rotating fresh-process engines; seven appearances in each position per slice",
    "operations": [
      "tpsa",
      "morgan",
      "tpsa_and_morgan",
      "tpsa_reused",
      "morgan_reused"
    ],
    "timing": "Sequential fresh processes; rotating engine and operation order; 1000 parse-plus-calculation calls, or 50 calls per prepared molecule on 1000 molecules, per repeat; native results retained; imports, file reads, normalization and comparison outside timer; reused-mode parsing and one preparation call per molecule also outside timer",
    "summary": "Median of five repeats per block, then median across 21 blocks; ratios are medians of paired block ratios",
    "bootstrap": "10000 paired resamples; fixed seed 114; percentile 95% intervals",
    "pilot": "One one-repeat pilot of three parse-inclusive operations preceded the formal run; two reused-molecule operations were added before formal timing; pilot samples were not pooled with formal results"
  },
  "agreement": {
    "all_formal_results_compared": true,
    "tpsa_absolute_tolerance": 1e-09,
    "tpsa_observed_max_absolute_error": 0.0,
    "morgan_all_2048_bits_equal": true,
    "example_numpy_matches_packed_bits": true,
    "sample_compounds": 3
  },
  "files": {
    "benchmark-results.json": "4b2f45bf360bf889f752239ba588bd85bd8374d86e5928c6d992a22619aa1cc7",
    "benchmark.py": "7c8358952edc5bb25a60d75b6b5a71654d66265496cd923e21f760efc70f3e6f",
    "features.csv": "d78f6fd6fb87768578b6ce400aa5c7c8a60b45c092f063472d6ba0572a54414c",
    "features.py": "8fa922a4fedc5265461c5180d832719918bc3ba37c815531db073f7c14288fc2",
    "morgan.npy": "9c026ddacfaa7b84049385a284c22372c7b7a671532d03a30c597caa6fbe980e",
    "tpsa.npy": "7f05a0a430cbae228086b8294a4cc553874411d961565db7c890290e08ba105b"
  }
}