{"id":"W2999962521","doi":"10.1002/mp.14033","title":"An artificial neural network to model response of a radiotherapy beam monitoring system","year":2020,"lang":"en","type":"article","venue":"Medical Physics","topic":"Advanced Radiotherapy Techniques","field":"Physics and Astronomy","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Princess Margaret Cancer Centre; Toronto Rehabilitation Institute; University of Toronto; University Health Network","funders":"","keywords":"Truebeam; Artificial neural network; Beam (structure); Collimator; Linear particle accelerator; Computer science; Backpropagation; Ionization chamber; Laser beam quality; Optics; Physics; Artificial intelligence","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":[0.0008795194,0.0008685424,0.0005186183,0.0005236539,0.0003438021,0.000640458,0.0008484409,0.001336135,0.002032092],"category_scores_gemma":[0.002040534,0.0003523203,0.0005194056,0.0004195551,0.0003231126,0.0006448817,0.0003236425,0.0008594065,0.0003507061],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001153609,"about_ca_system_score_gemma":0.0006055598,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01161922,"about_ca_topic_score_gemma":0.006010491,"domain_scores_codex":[0.9996612,0.0000965154,0.00002612815,0.00008978936,0.00007861597,0.0000477279],"domain_scores_gemma":[0.9992858,0.0003960104,0.00007394046,0.00002725878,0.0001987743,0.00001824439],"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":[0.00005087346,0.00003193213,0.0008247104,0.00002513929,0.00001747287,0.00002693962,0.00001359774,0.9904022,0.0007983946,0.0001865682,0.0001149098,0.007507223],"study_design_scores_gemma":[0.000001154732,0.00001229294,0.0001309134,0.000002341647,0.000002328973,0.000002437877,0.000001519673,0.9995406,0.0002091007,0.00005845623,0.0000374634,0.000001521137],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.323518,0.0009830568,0.6627353,0.0005655659,0.0002188753,0.0002174881,0.000373483,0.001484182,0.009904044],"genre_scores_gemma":[0.9704251,0.0001433707,0.02571302,0.00007267988,0.0000145618,0.0002062304,0.0001672408,0.00002035553,0.003237417],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01161922,"threshold_uncertainty_score":0.02310318,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02364781112145351,"score_gpt":0.3103051985428321,"score_spread":0.2866573874213785,"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."}}