{"id":"W3159861628","doi":"10.1016/j.nima.2021.165401","title":"An overview of the shielding optimization studies for the TRIUMF-ARIEL facility","year":2021,"lang":"en","type":"article","venue":"Nuclear Instruments and Methods in Physics Research Section A Accelerators Spectrometers Detectors and Associated Equipment","topic":"Radiation Therapy and Dosimetry","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":false,"ca_institutions":"TRIUMF","funders":"National Research Council Canada; Canada Foundation for Innovation; TRIUMF","keywords":"Electromagnetic shielding; Nuclear engineering; Cyclotron; Beam (structure); Linear particle accelerator; Proton; Monte Carlo method; Physics; Nuclear decommissioning; Computer science; Nuclear physics; Radiation transport; Upgrade; Shield; Radioactive waste; Environmental science; Electron; Engineering; Optics; Geology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001898081,0.0001337423,0.0003212896,0.0001157717,0.0004877538,0.00009981704,0.0000904531,0.0001023521,0.00003646595],"category_scores_gemma":[0.0005421719,0.00008747466,0.0001003564,0.000912286,0.0001660766,0.0001665286,0.00009319459,0.0003969115,8.534776e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003019089,"about_ca_system_score_gemma":0.00008087834,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004795324,"about_ca_topic_score_gemma":0.00001065396,"domain_scores_codex":[0.9979728,0.0007510417,0.0003249023,0.0003055037,0.0003730375,0.0002727321],"domain_scores_gemma":[0.9988233,0.0004814436,0.0001391859,0.0002345564,0.0002432778,0.00007821671],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0007299518,0.001095921,0.02672318,0.0004889954,0.001692386,0.000002269984,0.006502035,0.0008786793,0.5556644,0.001473851,0.00009159048,0.4046567],"study_design_scores_gemma":[0.01168286,0.004045191,0.1541717,0.0007370614,0.0004859641,0.00001877253,0.02114375,0.0802965,0.7137268,0.009921026,0.003007146,0.0007633098],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9953246,0.001207041,0.001993685,0.0003606535,0.000327935,0.0006975821,0.00001933944,0.00001718689,0.00005204121],"genre_scores_gemma":[0.986475,0.004919297,0.008254614,0.0001853349,0.00006920005,0.00004190478,0.00000672754,0.00001605827,0.00003188398],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4038934,"threshold_uncertainty_score":0.3751457,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2016830209589998,"score_gpt":0.4820626109827874,"score_spread":0.2803795900237876,"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."}}