{"id":"W2102515472","doi":"10.1016/j.ijrobp.2011.06.1609","title":"Clinical Implementation of Monte Carlo Designed Patient-Specific Compensators for Co-60 TBI Treatments","year":2011,"lang":"en","type":"article","venue":"International Journal of Radiation Oncology*Biology*Physics","topic":"Cardiac, Anesthesia and Surgical Outcomes","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University; Hôpital Maisonneuve-Rosemont","funders":"","keywords":"Supine position; Monte Carlo method; Beam (structure); Nuclear medicine; Medicine; Collimator; Monitor unit; Filter (signal processing); Biomedical engineering; Optics; Physics; Computer science; Surgery; Mathematics; Statistics","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":[0.0007680301,0.0004076384,0.0003095147,0.0003495384,0.0003331476,0.0006624148,0.0008846801,0.0006609723,0.004107929],"category_scores_gemma":[0.003573427,0.0003530093,0.0002483248,0.0003073279,0.0002400363,0.0002452694,0.0005087192,0.0004581709,0.0007258381],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007805218,"about_ca_system_score_gemma":0.001023161,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001826317,"about_ca_topic_score_gemma":0.002304711,"domain_scores_codex":[0.9997496,0.00008833154,0.00002115847,0.00003047578,0.00007988885,0.00003057613],"domain_scores_gemma":[0.9993113,0.0003333716,0.00009933318,0.00008177948,0.0001161484,0.00005801877],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.006260677,0.001028136,0.03312444,0.0004136108,0.0002302497,0.001120203,0.001200488,0.5286842,0.1628637,0.008361409,0.007000044,0.2497129],"study_design_scores_gemma":[0.0007164334,0.002271376,0.02238026,0.0000939653,0.0003256194,0.001834374,0.0003276226,0.8072432,0.1410385,0.002786939,0.02077132,0.0002104092],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4297124,0.0007938205,0.5469032,0.001047724,0.000219141,0.0008581802,0.0005196887,0.005213199,0.01473271],"genre_scores_gemma":[0.9280702,0.00009443767,0.06966726,0.0001411499,0.00001184319,0.0001711798,0.0001247072,0.0003315828,0.001387586],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004107929,"threshold_uncertainty_score":0.01374239,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06600570739384397,"score_gpt":0.4032356197821173,"score_spread":0.3372299123882733,"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."}}