{"id":"W2115661048","doi":"10.4103/0971-6203.139004","title":"A fast Monte Carlo code for proton transport in radiation therapy based on MCNPX","year":2014,"lang":"en","type":"article","venue":"Journal of Medical Physics","topic":"Radiation Therapy and Dosimetry","field":"Medicine","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University Health Centre","funders":"","keywords":"Monte Carlo method; Proton therapy; Bragg peak; Computational physics; Proton; Physics; Range (aeronautics); Computer science; Nuclear engineering; Nuclear medicine; Nuclear physics; Materials science; Mathematics; Engineering; Statistics","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":[0.001110636,0.00009937793,0.0003293357,0.00009776497,0.00002539641,0.000005919828,0.000104255,0.0001248201,0.00004486083],"category_scores_gemma":[0.000194289,0.00007129784,0.0001775051,0.0001541127,0.00003294031,0.00007368816,0.000001152209,0.0003567803,0.000001640007],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006534447,"about_ca_system_score_gemma":0.000250676,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000543617,"about_ca_topic_score_gemma":0.000002257003,"domain_scores_codex":[0.9984097,0.00006699869,0.000423258,0.00009634564,0.0008674288,0.0001362296],"domain_scores_gemma":[0.9991434,0.0002188187,0.0002322687,0.0001148288,0.00009207695,0.0001986697],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.008241679,0.002829668,0.06772307,0.0002838653,0.0001656276,0.00005121882,0.001305582,0.007091776,0.001154957,0.0005889495,0.003338575,0.907225],"study_design_scores_gemma":[0.08445711,0.0142688,0.172771,0.001636041,0.0001743361,0.00005059121,0.0001252014,0.5457333,0.03230735,0.003475853,0.1444448,0.0005556567],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9031282,0.0002722319,0.08062325,0.01401472,0.0004359063,0.00112118,0.00001303072,0.00001972534,0.000371725],"genre_scores_gemma":[0.9939712,0.0001549347,0.0002651298,0.0043486,0.001187322,0.00002267006,0.00000555933,0.00001778384,0.00002679626],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9066694,"threshold_uncertainty_score":0.2907442,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01981542159004068,"score_gpt":0.3109820729551647,"score_spread":0.291166651365124,"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."}}