{"id":"W2612496985","doi":"10.1002/mp.12338","title":"On mixed electron–photon radiation therapy optimization using the column generation approach","year":2017,"lang":"en","type":"article","venue":"Medical Physics","topic":"Advanced Radiotherapy Techniques","field":"Physics and Astronomy","cited_by":32,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University Health Centre; McGill University","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research","keywords":"Photon; Column generation; Radiation therapy; Column (typography); Electron; Dosimetry; Radiation; Medical physics; Physics; Materials science; Nuclear medicine; Medicine; Nuclear physics; Computer science; Optics; Mathematical optimization; Mathematics; Radiology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002034848,0.0001423818,0.0001440914,0.00001417699,0.0006683185,0.0001209552,0.0003213089,0.00006307629,0.0001065957],"category_scores_gemma":[0.00002050347,0.0001044452,0.00006973784,0.00005898918,0.0001134841,0.0002127295,0.00002172327,0.0002349546,0.000001235282],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006149602,"about_ca_system_score_gemma":0.00007826386,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000760242,"about_ca_topic_score_gemma":5.921758e-7,"domain_scores_codex":[0.9989945,0.00006901607,0.0001509841,0.0002195337,0.0003723816,0.000193635],"domain_scores_gemma":[0.9991635,0.00004125947,0.00021231,0.000479891,0.0000447133,0.00005829595],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001434564,0.001387457,0.009171273,0.00001359416,0.0003586669,0.000001567566,0.0007635825,0.1127998,0.01139584,0.08535291,0.00623366,0.7723781],"study_design_scores_gemma":[0.0009942224,0.0001136031,0.0002789486,0.00001365468,0.00001537822,5.774249e-7,0.000007356711,0.8949041,0.09283747,0.009056809,0.001527284,0.0002505358],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06825381,0.00004303186,0.929622,0.0001916322,0.0001570074,0.0003551734,0.000004330602,0.00004753479,0.001325498],"genre_scores_gemma":[0.9902292,0.00006665468,0.007302101,0.0002965645,0.001837264,0.00007242682,0.0001042402,0.0000356725,0.00005587689],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9223199,"threshold_uncertainty_score":0.5140234,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02453132783785343,"score_gpt":0.3049087308250999,"score_spread":0.2803774029872464,"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."}}