{"id":"W2766354236","doi":"10.1002/acm2.12210","title":"Time‐resolved diode dosimetry calibration through Monte Carlo modeling for <i>in vivo</i> passive scattered proton therapy range verification","year":2017,"lang":"en","type":"article","venue":"Journal of Applied Clinical Medical Physics","topic":"Radiation Therapy and Dosimetry","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University Health Centre","funders":"","keywords":"Monte Carlo method; Detector; Proton therapy; Calibration; Bragg peak; Dosimetry; Beam (structure); Optics; Dosimeter; Range (aeronautics); Ionization chamber; Physics; Proton; Materials science; Nuclear medicine; Radiation; Nuclear physics; Mathematics; Ionization; Medicine; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008852619,0.0004059544,0.0003351545,0.0002944907,0.000270613,0.0006358611,0.0007775805,0.0006097677,0.001075349],"category_scores_gemma":[0.0021891,0.0004855215,0.0004115477,0.0003374509,0.0002780638,0.0004209201,0.0002611756,0.0005200625,0.0002574867],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001254263,"about_ca_system_score_gemma":0.001152025,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00620629,"about_ca_topic_score_gemma":0.004618939,"domain_scores_codex":[0.9996643,0.0001051062,0.00001570264,0.00004350556,0.0001504987,0.0000208693],"domain_scores_gemma":[0.9991031,0.0004783865,0.0001300172,0.0001025005,0.0001677061,0.00001834461],"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":[0.00004030173,0.00002811272,0.001191832,0.00002398493,0.00001902399,0.00002440289,0.00004371496,0.984745,0.007975863,0.0008702182,0.0001156398,0.004922051],"study_design_scores_gemma":[0.000004858381,0.00001541715,0.0003331905,0.000003926044,0.000005985184,0.00001766421,0.000004056535,0.9924098,0.006544475,0.0001879383,0.0004660042,0.000006730093],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.2182074,0.0002702683,0.7746066,0.0001334141,0.00003308226,0.0001288308,0.0001818608,0.001305341,0.005133286],"genre_scores_gemma":[0.903079,0.0001578995,0.09479538,0.00004258225,0.000006007039,0.0001386435,0.0001125549,0.0002774255,0.001390519],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.00620629,"threshold_uncertainty_score":0.01234037,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06728725249978303,"score_gpt":0.3765096780720654,"score_spread":0.3092224255722824,"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."}}