{"id":"W3184462209","doi":"10.1088/1741-4326/ac14e6","title":"Modeling of ExB effects on tungsten re-deposition and transport in the DIII-D divertor","year":2021,"lang":"en","type":"article","venue":"Nuclear Fusion","topic":"Fusion materials and technologies","field":"Materials Science","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Fusion Energy Sciences; Office of Science; U.S. Department of Energy","keywords":"Divertor; DIII-D; Tungsten; Plasma; Impurity; Deposition (geology); Nuclear physics; Physics; Atomic physics; Tokamak; Nuclear engineering; Mechanics; Materials science; Geology; Metallurgy","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":[0.0002722062,0.0005587382,0.0004514539,0.0002715958,0.0005744603,0.0008542178,0.0009562565,0.001203029,0.001893429],"category_scores_gemma":[0.0007177988,0.0003918161,0.0005150671,0.0002755031,0.0005590756,0.0004654897,0.0005997959,0.0006180421,0.0003534683],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001320412,"about_ca_system_score_gemma":0.001097785,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0171139,"about_ca_topic_score_gemma":0.00751542,"domain_scores_codex":[0.9999152,0.0000170928,0.000003363734,0.00001543982,0.0000215109,0.00002744451],"domain_scores_gemma":[0.9998109,0.00007333086,0.00002456643,0.00001742285,0.00004025394,0.0000336088],"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":[0.00005479505,0.00002244022,0.001851451,0.00002547465,0.00001095315,0.0001310898,0.00005763303,0.9922283,0.003312031,0.001048745,0.0002817762,0.0009753422],"study_design_scores_gemma":[0.00001209299,0.00002200164,0.0005080654,0.000004075029,0.000003963589,0.00001741755,0.00002469838,0.9980323,0.000755985,0.0001677166,0.0004455818,0.000006170788],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9419086,0.0002555706,0.02674647,0.000371495,0.00006965853,0.0000780024,0.00108298,0.0003146523,0.0291726],"genre_scores_gemma":[0.9898685,0.0001295858,0.004797394,0.00005805621,0.000006297487,0.00008543507,0.0003920194,0.0000783107,0.004584378],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0171139,"threshold_uncertainty_score":0.03402859,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01259242746676541,"score_gpt":0.2140243283138656,"score_spread":0.2014319008471002,"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."}}