{"id":"W2112762027","doi":"10.1088/0031-9155/60/13/5007","title":"A study of potential numerical pitfalls in GPU-based Monte Carlo dose calculation","year":2015,"lang":"en","type":"article","venue":"Physics in Medicine and Biology","topic":"Advanced Radiotherapy Techniques","field":"Physics and Astronomy","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Centre hospitalier universitaire de Québec; Université Laval; Polytechnique Montréal","funders":"Natural Sciences and Engineering Research Council of Canada; Elekta; Compute Canada","keywords":"Monte Carlo method; Computer science; Benchmark (surveying); Rounding; Tracking (education); Voxel; Fraction (chemistry); Algorithm; Code (set theory); Computational science; Statistics; Mathematics; Artificial intelligence","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":[0.004145917,0.0005647089,0.0007240964,0.001043381,0.0007665002,0.001607637,0.001544416,0.0009117298,0.001392863],"category_scores_gemma":[0.05349049,0.0005063786,0.0004706656,0.001878142,0.0008506224,0.001254176,0.0009787775,0.0009697496,0.0002854202],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001401817,"about_ca_system_score_gemma":0.001447349,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00678513,"about_ca_topic_score_gemma":0.004322256,"domain_scores_codex":[0.9941427,0.002093967,0.0002952981,0.0003842055,0.002896228,0.0001876653],"domain_scores_gemma":[0.9688171,0.02274271,0.001998674,0.00274323,0.003490206,0.0002081213],"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":[0.00127552,0.0002684101,0.03425768,0.001043438,0.0002330325,0.001018577,0.001263249,0.7177821,0.03387437,0.01282103,0.003041243,0.1931213],"study_design_scores_gemma":[0.00006217067,0.0003614173,0.005422884,0.0001912701,0.00008414612,0.0007426835,0.0001930594,0.9467736,0.03688811,0.002448071,0.006779891,0.00005272212],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.702878,0.004757336,0.2757694,0.001222442,0.0003355625,0.0002675576,0.00023979,0.003364206,0.01116569],"genre_scores_gemma":[0.8522056,0.0006656001,0.1443781,0.0002000838,0.00003304014,0.00008901971,0.0001905838,0.001074051,0.001163837],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00678513,"threshold_uncertainty_score":0.02192599,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1117192219867781,"score_gpt":0.4045251327339424,"score_spread":0.2928059107471642,"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."}}