{"id":"W1131305499","doi":"10.1118/1.4924777","title":"SU‐E‐T‐416: Experimental Evaluation of a Commercial GPU‐Based Monte Carlo Dose Calculation Algorithm","year":2015,"lang":"en","type":"article","venue":"Medical Physics","topic":"Advanced Radiotherapy Techniques","field":"Physics and Astronomy","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Sunnybrook Health Science Centre","funders":"","keywords":"Imaging phantom; Linear particle accelerator; Monte Carlo method; Algorithm; Nuclear medicine; Voxel; Ionization chamber; Physics; Computer science; Beam (structure); Mathematics; Medicine; Optics; Ionization; Artificial intelligence","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":[0.001174606,0.0004262765,0.0003213682,0.0004627401,0.0002335517,0.0007364032,0.001181884,0.0005438466,0.004909061],"category_scores_gemma":[0.003277106,0.0002657796,0.0002397202,0.0008006625,0.0002750475,0.0004289287,0.0002856987,0.0004289226,0.0006327333],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001049644,"about_ca_system_score_gemma":0.0007017429,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007244544,"about_ca_topic_score_gemma":0.004845832,"domain_scores_codex":[0.9993159,0.0001606668,0.00003931238,0.00009704616,0.0003404084,0.00004668082],"domain_scores_gemma":[0.9983455,0.0006780236,0.00008967144,0.0001984561,0.0006067366,0.00008169031],"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":[0.005036567,0.001097528,0.01506007,0.0007118451,0.000231075,0.0003264546,0.0004673405,0.4572609,0.1989284,0.00508965,0.01409283,0.3016974],"study_design_scores_gemma":[0.0001892853,0.0008938737,0.004994236,0.00001662317,0.00003921228,0.0001689752,0.00003774656,0.9008919,0.08672135,0.000201625,0.005809424,0.00003579367],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7348797,0.0007607731,0.2274582,0.0003958641,0.0001995708,0.0004206611,0.001243717,0.008959904,0.0256815],"genre_scores_gemma":[0.875706,0.0001210235,0.1177446,0.0001295024,0.0000122962,0.0001311635,0.001199651,0.0009865272,0.003969281],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007244544,"threshold_uncertainty_score":0.01642245,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04666818167642817,"score_gpt":0.3691314580046902,"score_spread":0.322463276328262,"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."}}