{"id":"W2050818803","doi":"10.1088/0031-9155/50/5/021","title":"Assigning nonelastic nuclear interaction cross sections to Hounsfield units for Monte Carlo treatment planning of proton beams","year":2005,"lang":"en","type":"article","venue":"Physics in Medicine and Biology","topic":"Radiation Therapy and Dosimetry","field":"Medicine","cited_by":31,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Monte Carlo method; Hounsfield scale; Stopping power; Slab; Proton; Scaling; Materials science; Physics; Computational physics; Nuclear physics; Mathematics; Geometry; Statistics; Optics; Computed tomography; Medicine","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009984407,0.00008270958,0.0002382206,0.00009938394,0.00004842049,0.000002773007,0.00002209529,0.00006284439,0.000009261607],"category_scores_gemma":[0.00008843491,0.00005975076,0.00002156523,0.0001720116,0.00005399485,0.00004283003,0.000006467073,0.00008941345,9.570776e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004434515,"about_ca_system_score_gemma":0.0000208028,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001166534,"about_ca_topic_score_gemma":0.000008573293,"domain_scores_codex":[0.9995022,0.00002117331,0.0001918553,0.0001386557,0.00003454466,0.0001115786],"domain_scores_gemma":[0.9995567,0.000192551,0.00006426833,0.00007433736,0.0000636899,0.00004845048],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.007291301,0.001530886,0.3342699,0.0006433403,0.0008497165,0.00001123722,0.05132692,0.04807815,0.2369447,0.004271571,0.002245145,0.3125372],"study_design_scores_gemma":[0.06426614,0.09481645,0.1212751,0.004906627,0.001252064,0.0002394993,0.02414999,0.1471565,0.2971052,0.004136786,0.2389242,0.001771468],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9933978,0.000186725,0.004318462,0.0009916053,0.000138102,0.0005564042,0.000005974506,0.00001549037,0.0003894336],"genre_scores_gemma":[0.9981968,0.00005669635,0.0004327162,0.0005555177,0.0006092394,0.00006677659,0.0000150461,0.000008348266,0.00005881144],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3107658,"threshold_uncertainty_score":0.2436565,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2865697070780129,"score_gpt":0.4662102912145044,"score_spread":0.1796405841364915,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}