{"id":"W3207058645","doi":"10.1088/1361-6560/ac309f","title":"Monte Carlo calculation of the TG-43 dosimetry parameters for the INTRABEAM source with spherical applicators","year":2021,"lang":"en","type":"article","venue":"Physics in Medicine and Biology","topic":"Advanced Radiotherapy Techniques","field":"Physics and Astronomy","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Fonds de Recherche du Québec - Santé","keywords":"Dosimetry; Kerma; Monte Carlo method; Brachytherapy; Calibration; Nuclear medicine; Dose rate; Physics; Point source; Materials science; Computational physics; Optics; Medical physics; Mathematics; Medicine; Statistics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004079645,0.0002052915,0.0001702231,0.0002655111,0.0001942544,0.0003812089,0.0002984264,0.0004349018,0.002229531],"category_scores_gemma":[0.0008756542,0.0002135204,0.0003574793,0.0003353073,0.0001526165,0.0002251466,0.0001974765,0.0002818591,0.0005043977],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005927181,"about_ca_system_score_gemma":0.0005549846,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0022274,"about_ca_topic_score_gemma":0.002716936,"domain_scores_codex":[0.9998608,0.00003505542,0.000005381252,0.00001664401,0.00007113195,0.00001094967],"domain_scores_gemma":[0.9997162,0.0001295926,0.00004215612,0.00003183127,0.00007202731,0.000008222321],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001544135,0.0000478359,0.004776682,0.0001745171,0.00005213805,0.0001198207,0.0001611553,0.9202726,0.03881513,0.006929461,0.001161288,0.02733495],"study_design_scores_gemma":[0.00001711953,0.00006134856,0.003140636,0.00001466947,0.00002495565,0.0001316831,0.00002101453,0.9669783,0.02453665,0.00117919,0.003875443,0.00001903497],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3010783,0.000568484,0.6801573,0.0001300315,0.00003570516,0.0001719088,0.0005714831,0.001199838,0.01608693],"genre_scores_gemma":[0.8822919,0.0001927273,0.1139919,0.00004573782,0.000005128417,0.0001266666,0.0003850184,0.0003007295,0.002660149],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002229531,"threshold_uncertainty_score":0.007458568,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05379658325180586,"score_gpt":0.3483645222009771,"score_spread":0.2945679389491713,"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."}}