{"id":"W2205745377","doi":"10.1088/0029-5515/56/1/016021","title":"Simulation of gross and net erosion of high-Z materials in the DIII-D divertor","year":2015,"lang":"en","type":"article","venue":"Nuclear Fusion","topic":"Fusion materials and technologies","field":"Materials Science","cited_by":50,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Advanced Scientific Computing Research; Office of Science; Austrian Science Fund; National Natural Science Foundation of China; National Nuclear Security Administration; Chinesisch-Deutsche Zentrum für Wissenschaftsförderung; Sandia National Laboratories; Fusion Energy Sciences; U.S. Department of Energy","keywords":"Divertor; DIII-D; Materials science; Plasma; Erosion; Sputtering; Ionization; Atomic physics; Electric field; Tokamak; Ion; Nuclear physics; Physics; Nanotechnology; Thin film","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":[0.0002688143,0.0003276068,0.0003920401,0.0002364417,0.0002819644,0.0003677816,0.000676328,0.0006645619,0.00177402],"category_scores_gemma":[0.0006703339,0.0002449791,0.0002909512,0.00032664,0.0003929932,0.0001993834,0.000296401,0.0003316702,0.0001570469],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006555555,"about_ca_system_score_gemma":0.0003379123,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003242787,"about_ca_topic_score_gemma":0.001524125,"domain_scores_codex":[0.9999248,0.00001402416,0.000002906068,0.00001298208,0.0000234898,0.00002186427],"domain_scores_gemma":[0.9996849,0.0001706415,0.00003446624,0.00003026663,0.00004822436,0.00003149514],"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":[0.0002437183,0.0000473343,0.003032005,0.00007221488,0.00002308336,0.0001818957,0.00007209631,0.9795885,0.01376155,0.0009515308,0.0001923577,0.001833812],"study_design_scores_gemma":[0.00002632456,0.00009190822,0.001252265,0.000004527709,0.00000720334,0.00002861748,0.00002636805,0.990427,0.007667079,0.0001677305,0.0002921077,0.000008976893],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9846705,0.00007097307,0.009799413,0.00004979722,0.00001283101,0.00003273701,0.0003069157,0.0001569093,0.004899901],"genre_scores_gemma":[0.9964136,0.0000394597,0.002621585,0.00001367243,0.000001034608,0.00003751933,0.0001131046,0.00002057286,0.000739466],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003242787,"threshold_uncertainty_score":0.006447852,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02824265212239041,"score_gpt":0.2481808345686512,"score_spread":0.2199381824462608,"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."}}