{"id":"W1975801175","doi":"10.1118/1.4894921","title":"Poster - Thur Eve - 61: A new framework for MPERT plan optimization using MC-DAO","year":2014,"lang":"en","type":"article","venue":"Medical Physics","topic":"Radiation Therapy and Dosimetry","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria; BC Cancer Agency","funders":"","keywords":"Monte Carlo method; Computer science; Photon; Physics; Aperture (computer memory); Medical physics; Optics; Mathematics","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":[0.001119997,0.0009231353,0.0006933491,0.0007861392,0.0006539237,0.001484828,0.001798745,0.0007922707,0.01198941],"category_scores_gemma":[0.00223926,0.0006559201,0.001182043,0.0005489978,0.0005527823,0.0007941505,0.001412659,0.001464542,0.002769132],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007873698,"about_ca_system_score_gemma":0.001318501,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006487827,"about_ca_topic_score_gemma":0.009573043,"domain_scores_codex":[0.9995203,0.0001008098,0.00002546596,0.00006284074,0.0002564118,0.00003409275],"domain_scores_gemma":[0.9994899,0.0002040355,0.00003620727,0.00009297035,0.0001405699,0.00003629598],"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":[0.0001228098,0.00009766964,0.001006472,0.0002685963,0.0001463224,0.0001461619,0.0001562906,0.7010342,0.01063982,0.09319015,0.01380638,0.1793851],"study_design_scores_gemma":[0.00001561954,0.00001096637,0.0001176219,0.00001855595,0.000009760392,0.00003449983,0.00000679362,0.9718898,0.002063677,0.007155209,0.01866232,0.0000151829],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001196323,0.00009620095,0.9898144,0.00007107681,0.00003593156,0.00006023128,0.0001753545,0.004202225,0.004348238],"genre_scores_gemma":[0.05080575,0.000199353,0.9386261,0.0001234118,0.00005308458,0.0002765418,0.0005445707,0.004665703,0.004705503],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01198941,"threshold_uncertainty_score":0.04010856,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03575819186711339,"score_gpt":0.3189293275802002,"score_spread":0.2831711357130868,"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."}}