{
  "visual_id": "E01-posterior",
  "title": "Propagating a released nuclear posterior",
  "classification": "scoped_public_input_calculation",
  "run_ids": [
    "20260929T214425497398Z-E24-posterior"
  ],
  "claim_ids": [
    "C02"
  ],
  "input_files": [
    {
      "path": "runs/20260929T214425497398Z-E24-posterior/results.json",
      "sha256": "e6179b1edd32a778dfb3918d031e70cd43707bb65246cbf53fe01b4f8d475493"
    }
  ],
  "configurations": {
    "E24-posterior": {
      "seed": 24033,
      "draws_per_regulator": 192,
      "regulators_fm": [
        1.5,
        2.0,
        2.5
      ],
      "models": [
        "NLO-Full",
        "NLO-Reduced",
        "N3LO-Reduced"
      ],
      "source_commit": "0a8f4d8090f46d46d3a3b1807c5fb76cf1acdd21"
    }
  },
  "assumptions": {
    "E24-posterior": [
      "Source joint posterior samples encode the published likelihood, priors, correlations and theory-error hyperparameters; no refit or new likelihood is claimed.",
      "Eq.3--4 Gaussian Fourier transform in channel basis: q\u00b2=-Laplacian, S12(q)=-(gpp-gp/r)S12(r), i S.(k cross q)=-(gp/r)L.S.",
      "Deuteron binding and nn length were calibration data in the source. Computed posterior distributions are not independent held-out data.",
      "Selected draws retain correlations. A shuffled-column control deliberately destroys those correlations to measure their importance.",
      "Point radius and D probability are wavefunction diagnostics; precision electromagnetic radii require consistent currents.",
      "Parametric intervals and source Eq.34/53 truncation-inclusive predictive intervals are separate. The Gaussian error model permits negative binding predictions; these are not probabilities of an actual unbound Hamiltonian.",
      "The conditional truncation width uses each selected joint draw of Lambda_b and bar-c, retaining its correlation with the LECs; no median-hyperparameter substitution.",
      "Field derivatives are not sampled by an ordinary-phase LEC posterior."
    ]
  },
  "plotted_values": {
    "path": "E01-posterior-data.json",
    "sha256": "a8e3bea1b9220d238ac7f7c0a9d8bfd6c454ce6d0f978981596337168425102e"
  },
  "caption": "Nine source model/regulator combinations supply 225,000 singlet samples and 1,728 coupled deuteron solves. Binding and nn scattering were included in source calibration. Orange binding intervals marginalize the conditional Gaussian truncation model over the same joint LEC/hyperparameter draws; its negative draws are not probabilities of an alternative phase. Independently shuffling parameter columns is an intentionally invalid control that shows why covariance matters.",
  "alt_text": "EFT truncation widens deuteron intervals substantially. Shuffling the fitted couplings greatly broadens, and sometimes changes the sign of, inferred nn scattering lengths.",
  "generator": "src/metastable/public_report.py",
  "generator_sha256": "9e263878b7237d781a41d94693004412279b5cfa808ccd6e335b7b07269910d4",
  "generator_dependencies_sha256": {
    "src/metastable/render.py": "ff4837be5102588b6614aeb2b7880b10c0a0c20a155e2eb7b409014a47a3de01",
    "src/metastable/spin_report.py": "dd5c64c5c658938948672a7dc767aa02c34dde012c3fc4aedfc3642f88796847",
    "src/metastable/continuation_report.py": "f9bbce6d0e201a9f55c826d6e9c47ab901e51a71b4a1f962b52eb08a63ba5fe9",
    "src/metastable/refinement_report.py": "4539c0ec814603105ab3a2b5cc82ce291c0151113b5bd3916cdc235aadb9bfb0",
    "src/metastable/atomic_mass_report.py": "46dd1cdb56a5a02cafe001a1f6a7fb201e149461850df41e012f77a580c3694b",
    "src/metastable/closure_report.py": "b34a03a9e0058eed65722df542dbb92691dd138787e2078b43ee9f18e221f75c",
    "src/metastable/october_report.py": "f93e7f89e43165d8d25e2184b9b32e6e21c3e1ffe66020d35944f263aaecb726",
    "src/metastable/october_followup_report.py": "925d905ff3bddf97a7ace2f68a4a28e7dfea2238c4f81d891dda2a9e70c6d4f6",
    "src/metastable/october_dynamics_report.py": "6b8d84c0ce0d78f52d064c68697f0d9c885cdc736e215b54eba46821dbe59a33",
    "src/metastable/october_calibration_report.py": "f714ef7ccfaa26e847c6135054f53528b3ff1d7096e7d113cffeea333e77e3d2",
    "src/metastable/october_interface_report.py": "2fc8826a33c952d7898154f84830748c26842c9a165d14aa7b7fb9721fac00bd",
    "src/metastable/october_checkpoint8_report.py": "f3b54f23510b9bfeffc5ff04e6df54e967228f43ba25a15e12e34f898cdfe0af",
    "src/metastable/october_checkpoint9_report.py": "4bd987aac59964ccb4768a95e0cb6f7d1fdccbeffe9483860da7b431f2224ae4",
    "src/metastable/october_checkpoint10_report.py": "9da673d773b63298e041914447ffd97065c1cf2b8966c90fc4ebcbee25a0ed63",
    "src/metastable/october_checkpoint11_report.py": "5f01064f02f4c76d0059d348a763b285c92c3677e6cb0ba0bbf7faa1a4b98248",
    "src/metastable/october_checkpoint12_report.py": "46022030652e3a1e274dfd27b36dfab25d90a97fde439b1da44d6f1fdc5140b5",
    "src/metastable/october_checkpoint13_report.py": "997c59be3af1b6b7be95fd4314e0f3b98c562629901a639572284045a65980c2",
    "src/metastable/october_checkpoint14_report.py": "d84de7d8516d8a4d8e21b5f9f279476f3035f719c1c8ab03b7ac1e44bf822240",
    "src/metastable/october_checkpoint15_report.py": "1f6e17b9549dc31fbb58ba578c4d8ed8e219b4ad30810df0a9d7d2d00e63efdc",
    "src/metastable/october_checkpoint16_report.py": "74cb8aac45d1d5ce0e6eb6678e9b6cdf98cd46fd6e264a513b612ab763fcd034",
    "src/metastable/october_checkpoint17_report.py": "9daceb74e91f6f8db0f7d89929226d46c464c284d06d0694f525fecf0c736bf6",
    "src/metastable/october_checkpoint18_report.py": "f33f88e316cae93af87cef75d8df41ce82970c8f8bc466dd7a094a92c5f00f8b",
    "src/metastable/october_checkpoint19_report.py": "ce2250507145354b6478cafaaff98c2b8ae2795c3c309f0d903a920365a77090",
    "src/metastable/october_checkpoint20_report.py": "e2ea0a8a374036254008cf6de8f10352dfb2585c4ccb18c1e850c017e6128294",
    "src/metastable/october_checkpoint21_report.py": "596b873676167227b2c92d358fcdbc0614908a5a9daad1da6227b81fce203eec",
    "src/metastable/publication_files.py": "e68bd0ee4e849a72fa828f0cfcf34cb6b1b9f2a8bbdbb3d51085054915039607"
  },
  "command": "python run.py full public-report",
  "output_sha256": {
    "svg": "d9e1f6570d15e95dc049e1b27de09661ec4a5380c4b3c0ecf16f15b8b2496737",
    "png": "ea045c6f92b18b9fbc44d4979cb55c0d7fbe9842f766f192796d430fc162f504"
  }
}