{"id":"W2467669285","doi":"10.1118/1.4957780","title":"WE‐AB‐209‐11: Prostate Cancer Treatment Planning: Sensitivity and Representative Objective Function Weights","year":2016,"lang":"en","type":"article","venue":"Medical Physics","topic":"Prostate Cancer Treatment and Research","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Princess Margaret Cancer Centre; University of Toronto","funders":"","keywords":"Radiation treatment planning; Centroid; Cluster analysis; Medical imaging; Medicine; Mathematics; Mathematical optimization; Computer science; Nuclear medicine; Algorithm; Statistics; Artificial intelligence; Radiology; Radiation therapy","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":[0.001925229,0.0006671463,0.0005402777,0.0005403198,0.0003870325,0.0007162553,0.0007992416,0.00079418,0.0018123],"category_scores_gemma":[0.005574707,0.0005853359,0.0007751039,0.0004725906,0.000569137,0.0004764069,0.0006890693,0.0008211855,0.0002715424],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001417025,"about_ca_system_score_gemma":0.001787559,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008003085,"about_ca_topic_score_gemma":0.008540918,"domain_scores_codex":[0.9988208,0.000430153,0.00005066693,0.0001624556,0.000466514,0.00006924543],"domain_scores_gemma":[0.9982449,0.001084119,0.0002156387,0.0001850416,0.0002304194,0.00003998868],"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":[0.00008894248,0.00006068064,0.001832215,0.00006483014,0.00005479963,0.00005443279,0.00008239951,0.9260604,0.005500234,0.001575096,0.0009863235,0.06363957],"study_design_scores_gemma":[0.00001892369,0.00005054964,0.001100858,0.000008699383,0.00001194762,0.00009202248,0.00001120819,0.9894508,0.006438585,0.001705062,0.00109462,0.00001678762],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05193833,0.00013417,0.9434696,0.0001965515,0.00001489213,0.0001572433,0.0001466741,0.001415847,0.002526727],"genre_scores_gemma":[0.5058717,0.00007702733,0.4915039,0.0001455525,0.00002072129,0.0002779817,0.0002939676,0.0005098297,0.001299211],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008003085,"threshold_uncertainty_score":0.01591301,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03619136844100977,"score_gpt":0.3532843084433435,"score_spread":0.3170929400023337,"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."}}