{"id":"W1948818604","doi":"10.3233/jcm-2011-0358","title":"A performance evaluation on monte carlo simulation for radiation dosimetry using cell processor","year":2011,"lang":"en","type":"article","venue":"Journal of Computational Methods in Sciences and Engineering","topic":"Advanced Radiotherapy Techniques","field":"Physics and Astronomy","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University; Princess Margaret Cancer Centre; University of Toronto","funders":"","keywords":"Computer science; PowerPC; Monte Carlo method; Parallel computing; Acceleration; Graphics; Hardware acceleration; Computational science; General-purpose computing on graphics processing units; Code (set theory); Computer architecture; Embedded system; Operating system; Field-programmable gate array; Software; Programming language; Physics","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":[0.0007608519,0.0003344278,0.0004878941,0.0003590348,0.0003800291,0.0005410472,0.0005569509,0.0004726309,0.001833951],"category_scores_gemma":[0.00356727,0.0001633575,0.0002219657,0.0009962551,0.0002463005,0.0005724595,0.0002726312,0.0003090297,0.0003359781],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006762471,"about_ca_system_score_gemma":0.0007875789,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005988982,"about_ca_topic_score_gemma":0.002990713,"domain_scores_codex":[0.9994553,0.0002051396,0.0000191267,0.0000616882,0.0001880045,0.00007067219],"domain_scores_gemma":[0.9975454,0.00159826,0.00006619808,0.0001891341,0.0005342138,0.00006674082],"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":[0.001110164,0.000147933,0.009787098,0.0002000884,0.00007774835,0.0002052182,0.0002398763,0.8855549,0.03547461,0.008168845,0.001872786,0.05716076],"study_design_scores_gemma":[0.00002051367,0.0001925611,0.001127577,0.000007837404,0.00002234482,0.00004184163,0.0000421632,0.9784896,0.01833627,0.0004213479,0.00128331,0.00001456399],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8814158,0.001205124,0.1022162,0.0002437697,0.00008128597,0.00009361688,0.0003750701,0.001674342,0.0126948],"genre_scores_gemma":[0.9732273,0.0002565736,0.02502308,0.0000363373,0.000007525649,0.00003185423,0.0002353462,0.0001672074,0.001014812],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005988982,"threshold_uncertainty_score":0.01190823,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07852798369715379,"score_gpt":0.4225686909454413,"score_spread":0.3440407072482875,"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."}}