{"id":"W2906877419","doi":"10.1002/mp.13368","title":"A fast inverse direct aperture optimization algorithm for intensity‐modulated radiation therapy","year":2018,"lang":"en","type":"article","venue":"Medical Physics","topic":"Advanced Radiotherapy Techniques","field":"Physics and Astronomy","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University; London Health Sciences Centre; Western University","funders":"Canadian Institutes of Health Research; Government of Ontario","keywords":"Algorithm; Imaging phantom; Computer science; Aperture (computer memory); Optimization problem; Inverse; Mathematical optimization; Mathematics; Optics; Physics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008170019,0.0005998954,0.0004275116,0.0003234516,0.0002796268,0.0005581303,0.0006629558,0.0006189673,0.002611029],"category_scores_gemma":[0.001814464,0.000346259,0.0005641427,0.0003106555,0.0003181524,0.000571228,0.0006011554,0.0008447816,0.0006999139],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006818157,"about_ca_system_score_gemma":0.0009664692,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002301945,"about_ca_topic_score_gemma":0.002060415,"domain_scores_codex":[0.9995803,0.0001013064,0.00001939797,0.00005017928,0.0002272487,0.00002154466],"domain_scores_gemma":[0.9995358,0.0001928321,0.00003927295,0.00003703615,0.0001815215,0.00001359055],"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":[0.0001229383,0.00005201403,0.0004490206,0.0001947419,0.000047523,0.00005498441,0.0001208608,0.5843078,0.02535823,0.01471835,0.002862278,0.3717113],"study_design_scores_gemma":[0.00001814443,0.00003883687,0.0001275166,0.00001106751,0.000005511183,0.00004303658,0.000004915454,0.9888079,0.003996221,0.00150327,0.005435029,0.000008518021],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.002167012,0.0001123824,0.9963719,0.00003359634,0.000017683,0.00003284629,0.0000108503,0.0003107659,0.0009430575],"genre_scores_gemma":[0.06446355,0.0001364233,0.9332516,0.00004232646,0.00001476217,0.0001648997,0.00007419724,0.0001635262,0.001688703],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002611029,"threshold_uncertainty_score":0.008734822,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00953140301718689,"score_gpt":0.2694870397166586,"score_spread":0.2599556366994717,"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."}}