{"id":"W2145779611","doi":"10.1088/0031-9155/57/5/1375","title":"Fast online Monte Carlo-based IMRT planning for the MRI linear accelerator","year":2012,"lang":"en","type":"article","venue":"Physics in Medicine and Biology","topic":"Advanced Radiotherapy Techniques","field":"Physics and Astronomy","cited_by":55,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal","funders":"Stichting voor de Technische Wetenschappen; Nederlandse Organisatie voor Wetenschappelijk Onderzoek; Nvidia","keywords":"Imaging phantom; Monte Carlo method; Linear particle accelerator; Computer science; Radiation treatment planning; Medical physics; Nuclear medicine; Radiation therapy; Physics; Beam (structure); Mathematics; Medicine; Radiology; Optics","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":[0.0004411148,0.0005683072,0.0004560967,0.0003896174,0.0002795444,0.0007387896,0.0008302974,0.0005499337,0.00467438],"category_scores_gemma":[0.001361452,0.0005023841,0.0004511977,0.000414401,0.0002947396,0.0004097328,0.0005978115,0.0007091694,0.001311598],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000704596,"about_ca_system_score_gemma":0.001079352,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004084131,"about_ca_topic_score_gemma":0.004930835,"domain_scores_codex":[0.9996736,0.00009013098,0.00001673164,0.00003483825,0.0001600398,0.00002466661],"domain_scores_gemma":[0.9995669,0.0002061097,0.0000497094,0.00007172662,0.00008383868,0.00002176505],"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":[0.0004663081,0.0000820509,0.001131669,0.0002451717,0.00008690983,0.000184657,0.0001744056,0.7172501,0.04992693,0.01066113,0.00733688,0.2124538],"study_design_scores_gemma":[0.00004100856,0.00004717523,0.0005809175,0.00001629899,0.0000206312,0.0001544631,0.000009164508,0.9706668,0.01704855,0.002591747,0.008793046,0.0000302168],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.005989965,0.0002495363,0.9871542,0.00006767802,0.00001949365,0.00005093728,0.00009415618,0.002939338,0.003434673],"genre_scores_gemma":[0.2152514,0.0002415516,0.7788454,0.0001022412,0.00002312089,0.0001915605,0.0003532195,0.001351776,0.003639868],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.00467438,"threshold_uncertainty_score":0.01563734,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1869119983454362,"score_gpt":0.4401562785949011,"score_spread":0.253244280249465,"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."}}