{"id":"W3011670721","doi":"10.1088/1361-6560/ab7eef","title":"Technical note: development and validation of a Monte Carlo tool for analysis of patient-generated photon scatter","year":2020,"lang":"en","type":"article","venue":"Physics in Medicine and Biology","topic":"Advanced Radiotherapy Techniques","field":"Physics and Astronomy","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba; CancerCare Manitoba","funders":"Natural Sciences and Engineering Research Council of Canada; CancerCare Manitoba Foundation","keywords":"Monte Carlo method; Photon; Physics; Fluence; Imaging phantom; Optics; Computational physics; Beam (structure); Bremsstrahlung; Compton scattering; Computer science; Statistics; Mathematics; Laser","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":[0.002883142,0.0007130977,0.0004120116,0.0008474588,0.0004291913,0.0008740653,0.001988578,0.0007975005,0.009399701],"category_scores_gemma":[0.01043382,0.0004637261,0.0006451018,0.0004901745,0.000384498,0.0005745433,0.0007406302,0.000778778,0.003188722],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007569708,"about_ca_system_score_gemma":0.001523861,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003497083,"about_ca_topic_score_gemma":0.002759935,"domain_scores_codex":[0.9987546,0.0002757789,0.000101535,0.0001360148,0.000675314,0.0000567384],"domain_scores_gemma":[0.9935443,0.0028087,0.000229941,0.0007676317,0.002506428,0.0001429967],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001071839,0.0003204973,0.01364176,0.0006764212,0.0002440718,0.000986997,0.000709397,0.3856467,0.1137196,0.01998835,0.04180924,0.421185],"study_design_scores_gemma":[0.000127536,0.0001239997,0.002507995,0.00006410379,0.00003637327,0.0005598689,0.0000276223,0.8664448,0.09230313,0.001435096,0.03628081,0.00008877416],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01192937,0.0001016293,0.9677854,0.0001582749,0.00006988854,0.0002291668,0.0005857692,0.0170528,0.002087749],"genre_scores_gemma":[0.1287173,0.0001161897,0.8579788,0.0001895817,0.0000373547,0.0006419942,0.001422117,0.006913784,0.003982942],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.009399701,"threshold_uncertainty_score":0.03144515,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0774332369989213,"score_gpt":0.3641553051026462,"score_spread":0.2867220681037249,"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."}}