{"id":"W4243019352","doi":"10.32920/ryerson.14648943","title":"Machine Learning Optimization for Prostate Brachytherapy Treatment Planning","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Advanced X-ray and CT Imaging","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Brachytherapy; Prostate brachytherapy; Computer science; Radiation treatment planning; Prostate; Artificial intelligence; Medical physics; Medicine; Radiology; Radiation therapy; Internal 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001294706,0.0008377678,0.001589429,0.0007069609,0.0005505609,0.001086751,0.0009480778,0.001591722,0.00404589],"category_scores_gemma":[0.005366736,0.001083908,0.001038846,0.001094788,0.0008631916,0.0009026513,0.001112465,0.001888755,0.0006536769],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001640028,"about_ca_system_score_gemma":0.001365315,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009709366,"about_ca_topic_score_gemma":0.005351593,"domain_scores_codex":[0.9993235,0.0002983826,0.0000245011,0.000093815,0.0002138616,0.00004600639],"domain_scores_gemma":[0.9984099,0.001151648,0.00008840258,0.00007063693,0.0002361835,0.00004330874],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001981741,0.00001240183,0.00007033483,0.0000403614,0.00001675681,0.0000104583,0.00001293089,0.9768091,0.0003784908,0.003948353,0.001293057,0.01738792],"study_design_scores_gemma":[0.000002492058,0.000003351788,0.00004422784,0.000003630494,0.00000200031,0.000003845809,0.00000135676,0.9959812,0.0001486954,0.003429051,0.0003780554,0.000002048919],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.007514524,0.00128514,0.9846944,0.000853156,0.00009729707,0.00005069864,0.0001314606,0.000394905,0.004978369],"genre_scores_gemma":[0.4925226,0.001239634,0.4777994,0.0005368834,0.0003521671,0.0003926567,0.0006621784,0.001102979,0.02539141],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.009709366,"threshold_uncertainty_score":0.01930571,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01549497102531102,"score_gpt":0.2637604596583717,"score_spread":0.2482654886330607,"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."}}