{"id":"W4409874998","doi":"10.1088/1361-6560/add1a8","title":"A systematic characterization of plastic scintillation dosimeters response in magnetic fields: II. Monte Carlo simulations","year":2025,"lang":"en","type":"article","venue":"Physics in Medicine and Biology","topic":"Radiation Effects and Dosimetry","field":"Agricultural and Biological Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Rio Tinto (Canada); Héma-Québec; Université de Montréal; Université Laval; Natural Sciences and Engineering Research Council of Canada; Université du Québec à Montréal; Centre Hospitalier de l’Université de Montréal; Hôtel-Dieu de Québec","funders":"Natural Sciences and Engineering Research Council of Canada; Mitacs","keywords":"Monte Carlo method; Physics; Cherenkov radiation; Computational physics; Magnetic field; Electron; Fluence; Nuclear physics; Statistical physics; Optics; Quantum mechanics","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":[0.0006770345,0.0003946849,0.0003663385,0.000434563,0.0003078208,0.0003969266,0.00053012,0.0006110744,0.001063709],"category_scores_gemma":[0.002319995,0.0002869003,0.0003615887,0.000443252,0.0003073423,0.0003144368,0.0002133031,0.0003410527,0.0001695835],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006349231,"about_ca_system_score_gemma":0.0005926961,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004978045,"about_ca_topic_score_gemma":0.003113907,"domain_scores_codex":[0.9997638,0.0000656025,0.00001390225,0.00003064335,0.00009575157,0.00003032924],"domain_scores_gemma":[0.9985952,0.0008281964,0.0001364588,0.0001592062,0.0002546002,0.00002631859],"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":[0.0001404833,0.00005433694,0.005201421,0.0001037558,0.0000510868,0.00006095037,0.0000621764,0.968188,0.01920033,0.001634227,0.0002713515,0.00503199],"study_design_scores_gemma":[0.00001365554,0.00007021832,0.001688872,0.00001200789,0.00001366077,0.00002920908,0.00001630052,0.9786175,0.01854225,0.0003418487,0.000640657,0.00001362552],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.917882,0.000467754,0.0731247,0.0001769456,0.00003744015,0.0001192055,0.0008235556,0.0007535309,0.006614903],"genre_scores_gemma":[0.988043,0.0001240486,0.01072709,0.0000369781,0.000005822271,0.00008604919,0.000292342,0.0000796892,0.000605122],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004978045,"threshold_uncertainty_score":0.009898126,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05075374796709661,"score_gpt":0.3093906559938842,"score_spread":0.2586369080267876,"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."}}