{"id":"W2419216225","doi":"","title":"A study to determine the optimal input parameters for the Monte Carlo simulation of a clinical linear accelerator","year":2016,"lang":"en","type":"other","venue":"DR-NTU (Nanyang Technological University)","topic":"Advanced Radiotherapy Techniques","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Monte Carlo method; Linear particle accelerator; Computer science; Linear model; Statistical physics; Mathematics; Statistics; Physics; Beam (structure)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002722895,0.0003167943,0.0005723663,0.0002534268,0.0001372009,0.00001703703,0.001169535,0.0002815236,0.00016734],"category_scores_gemma":[0.00008349136,0.0001716876,0.0003275644,0.0003779608,0.0003892482,0.00005347515,0.0003288384,0.000380675,0.00000612917],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004787596,"about_ca_system_score_gemma":0.00004143202,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006345694,"about_ca_topic_score_gemma":0.000015506,"domain_scores_codex":[0.9985797,0.0001145626,0.0003425546,0.0004960157,0.0001761963,0.0002909679],"domain_scores_gemma":[0.9978192,0.0008047752,0.0004234097,0.0008089204,0.00008238629,0.00006123547],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.002564579,0.00515878,0.03690128,0.00009010592,0.005908056,0.0001428662,0.0009093185,0.0160315,0.0004624296,0.02632384,0.07853142,0.8269758],"study_design_scores_gemma":[0.001511402,0.001151055,0.0001437834,0.0001057605,0.0002430781,4.344861e-7,0.0007678669,0.004276135,0.0003139887,0.0001852908,0.9908247,0.0004764799],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05195497,0.0001132925,0.9284059,0.0009010292,0.0002865831,0.007383867,0.0004046771,0.001195609,0.009354086],"genre_scores_gemma":[0.8176295,0.00008102565,0.04794456,0.0001446703,0.0005692118,0.0001183924,0.000008748008,0.000345043,0.1331588],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9122933,"threshold_uncertainty_score":0.7001218,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05748872489824997,"score_gpt":0.3472857675805708,"score_spread":0.2897970426823208,"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."}}