{"id":"W2013215584","doi":"10.1118/1.4914140","title":"Models for predicting objective function weights in prostate cancer IMRT","year":2015,"lang":"en","type":"article","venue":"Medical Physics","topic":"Prostate Cancer Diagnosis and Treatment","field":"Medicine","cited_by":68,"is_retracted":false,"has_abstract":true,"ca_institutions":"Princess Margaret Cancer Centre; Ontario Institute for Cancer Research; University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Rectum; Mathematics; Logistic regression; Prostate; Population; Nuclear medicine; Medicine; Statistics; Cancer; Surgery; Internal medicine","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":[0.002135733,0.001032361,0.0006847787,0.0009982336,0.000201193,0.00059461,0.0009522497,0.0006120402,0.0009085243],"category_scores_gemma":[0.007346209,0.0004661212,0.0006568685,0.0005820048,0.0003151342,0.0005531618,0.000526085,0.0009415743,0.0003897099],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001143377,"about_ca_system_score_gemma":0.0007323571,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008678779,"about_ca_topic_score_gemma":0.007465924,"domain_scores_codex":[0.9993885,0.0002169923,0.0000289781,0.0001464947,0.0001677807,0.00005129429],"domain_scores_gemma":[0.997795,0.00137858,0.0003231508,0.00009288079,0.000365864,0.00004450158],"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":[0.00005385179,0.00003967072,0.005857611,0.0000235244,0.00004880607,0.0000216637,0.00001674591,0.9608842,0.0006535506,0.0003519406,0.0002714896,0.03177694],"study_design_scores_gemma":[0.000002878891,0.00001766066,0.0006846598,0.000004127126,0.000004606812,0.000007886457,0.000001672411,0.9985808,0.0002580673,0.0003476754,0.00008673353,0.000003216097],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2737186,0.001021739,0.7210335,0.0004505049,0.00005563536,0.0001420127,0.0004796389,0.00121959,0.001878802],"genre_scores_gemma":[0.9119841,0.0002429528,0.08505886,0.0001175056,0.00004439334,0.0002582418,0.0005745881,0.00009410896,0.001625156],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008678779,"threshold_uncertainty_score":0.01725656,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03692649340942879,"score_gpt":0.3065094244144591,"score_spread":0.2695829310050303,"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."}}