{"id":"W2163995950","doi":"10.1016/j.ijrobp.2014.06.036","title":"Establishing High-Quality Prostate Brachytherapy Using a Phantom Simulator Training Program","year":2014,"lang":"en","type":"article","venue":"International Journal of Radiation Oncology*Biology*Physics","topic":"Prostate Cancer Diagnosis and Treatment","field":"Medicine","cited_by":48,"is_retracted":false,"has_abstract":false,"ca_institutions":"BC Cancer Agency; Interior Health","funders":"","keywords":"Quality assurance; Imaging phantom; Medicine; Brachytherapy; Medical physics; Radiation treatment planning; Prostate brachytherapy; Consistency (knowledge bases); Nuclear medicine; Radiation therapy; Radiology; Computer science; Artificial intelligence","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":[0.003840072,0.0006899807,0.000338824,0.0007216834,0.002014512,0.0007701511,0.001596921,0.0009530322,0.006384115],"category_scores_gemma":[0.00572655,0.0005768798,0.0006396016,0.0003299161,0.0005115253,0.0007720267,0.002448514,0.001382334,0.00190928],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001537955,"about_ca_system_score_gemma":0.009862015,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003386502,"about_ca_topic_score_gemma":0.009281854,"domain_scores_codex":[0.9985059,0.0005475638,0.00007896993,0.0002070649,0.0004312601,0.0002292453],"domain_scores_gemma":[0.9953417,0.0007365549,0.0002757635,0.0007269976,0.001122894,0.001796149],"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":[0.003366623,0.07351941,0.1347537,0.0004229486,0.0001018976,0.001565925,0.006538952,0.04402456,0.2447506,0.001820343,0.01109113,0.4780439],"study_design_scores_gemma":[0.002305695,0.125901,0.4029235,0.0003692599,0.0003819978,0.006966788,0.00880992,0.1223542,0.2010595,0.002871439,0.1254362,0.0006204839],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9172291,0.00009107829,0.05782775,0.000954096,0.0001684659,0.006098108,0.0002975003,0.001461305,0.01587263],"genre_scores_gemma":[0.8288546,0.0001491227,0.1557537,0.0003670491,0.00007093551,0.002134749,0.000597524,0.0002076342,0.01186467],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006384115,"threshold_uncertainty_score":0.02135694,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05220819007465308,"score_gpt":0.4033620554162939,"score_spread":0.3511538653416408,"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."}}