{"id":"W2048294709","doi":"10.1118/1.4736423","title":"Direct aperture optimization for FLEC‐based MERT and its application in mixed beam radiotherapy","year":2012,"lang":"en","type":"article","venue":"Medical Physics","topic":"Advanced Radiotherapy Techniques","field":"Physics and Astronomy","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Canadian Institutes of Health Research; Terry Fox Foundation; National University of Ireland; Natural Sciences and Engineering Research Council of Canada; McGill University","keywords":"Computer science; Dosimetry; Radiation treatment planning; Radiation therapy; Medical physics; Aperture (computer memory); Collimator; Photon; Nuclear medicine; Optics; Physics; Medicine; Radiology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.0004466825,0.0004355745,0.0002657221,0.0003867748,0.0001576338,0.0004421721,0.0003515122,0.0003620021,0.001029559],"category_scores_gemma":[0.0009502088,0.0002915685,0.0004071178,0.0002818817,0.0002153453,0.0002945002,0.000560668,0.000317901,0.0001830227],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005931117,"about_ca_system_score_gemma":0.0004934361,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001041581,"about_ca_topic_score_gemma":0.00175862,"domain_scores_codex":[0.9997177,0.00004942706,0.00001451448,0.00004332207,0.0001583991,0.00001667084],"domain_scores_gemma":[0.9997012,0.0001381661,0.00005892237,0.00003195748,0.00005526426,0.00001445269],"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":[0.0003022977,0.0001233939,0.004466303,0.0004012749,0.00008299681,0.0001711555,0.0002398311,0.6111054,0.1612624,0.008024769,0.000889476,0.2129307],"study_design_scores_gemma":[0.00003781181,0.0001872159,0.002399913,0.00002320719,0.00003363174,0.0003288155,0.00002095055,0.9436306,0.04539447,0.001345159,0.006563997,0.00003426186],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1102943,0.0007731669,0.8830034,0.00008598168,0.00002333771,0.00008779374,0.00005918831,0.0004842158,0.005188658],"genre_scores_gemma":[0.5073029,0.0002015585,0.489893,0.00004359299,0.00001076366,0.00007962459,0.00009324847,0.0002180289,0.002157162],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.001041581,"threshold_uncertainty_score":0.004303336,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009219582908498204,"score_gpt":0.2842347624824522,"score_spread":0.275015179573954,"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."}}