{"id":"W4292488321","doi":"10.1002/mp.15922","title":"Knowledge‐based planning algorithm for lung SBRT with robust Bayesian stochastic frontier analysis and missing data management","year":2022,"lang":"en","type":"article","venue":"Medical Physics","topic":"Advanced Radiotherapy Techniques","field":"Physics and Astronomy","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"","keywords":"Missing data; Radiation treatment planning; Computer science; Bayesian probability; Bronchus; Algorithm; Data mining; Medicine; Radiology; Artificial intelligence; Lung; Radiation therapy; Machine learning; Respiratory disease; 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":[0.002068866,0.0008765904,0.001970594,0.001513691,0.0005911762,0.00114692,0.001686084,0.001568636,0.002592678],"category_scores_gemma":[0.005745407,0.0008284915,0.001618511,0.001331476,0.0006226666,0.0009027038,0.001460818,0.001693852,0.0004939752],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001581392,"about_ca_system_score_gemma":0.00281937,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01818525,"about_ca_topic_score_gemma":0.009965671,"domain_scores_codex":[0.9993547,0.000210122,0.00004347641,0.0001395158,0.0001685836,0.00008367919],"domain_scores_gemma":[0.9976205,0.001804536,0.0001871552,0.00007755572,0.0002378961,0.00007234106],"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":[0.00004530881,0.00002784784,0.0004694786,0.00003621653,0.00002996409,0.00003866994,0.00003288226,0.9669393,0.0002263402,0.001556022,0.0005038654,0.0300942],"study_design_scores_gemma":[0.000007544002,0.00001276798,0.00006856185,0.000004621827,0.000005046997,0.000007535107,0.000003939788,0.997929,0.0000966136,0.001756428,0.0001049085,0.000003084335],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.008466229,0.0001503788,0.9900975,0.0001663399,0.000009975692,0.00004757194,0.00014218,0.0004330192,0.0004868408],"genre_scores_gemma":[0.5344725,0.0002490333,0.4616782,0.0002371054,0.00005726887,0.0006185581,0.001026107,0.000189538,0.00147177],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01818525,"threshold_uncertainty_score":0.0361588,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02022512933941703,"score_gpt":0.3094593926643334,"score_spread":0.2892342633249163,"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."}}