{"id":"W4388934314","doi":"10.1088/2053-1591/ad0f43","title":"Recent DIII-D progress toward validating models of tungsten erosion, re-deposition, and migration for application to next-step fusion devices","year":2023,"lang":"en","type":"article","venue":"Materials Research Express","topic":"Fusion materials and technologies","field":"Materials Science","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canada Research Chairs; University of Toronto; University of New Brunswick","funders":"National Nuclear Security Administration; Office of Science; Honeywell; U.S. Department of Energy","keywords":"DIII-D; Tungsten; Deposition (geology); Erosion; Fusion; Environmental science; Materials science; Nuclear engineering; Computer science; Geology; Engineering; Metallurgy; Tokamak; Geomorphology; Physics; Nuclear physics; Plasma; Philosophy","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00298761,0.0002035447,0.0003954312,0.000353949,0.0004112411,0.0005771747,0.0005239876,0.0001847879,0.00008846328],"category_scores_gemma":[0.0003893995,0.0001694302,0.00003126763,0.0005416,0.000186166,0.0005065985,0.0008505087,0.00006386668,0.00005421112],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004949447,"about_ca_system_score_gemma":0.00004158847,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003185354,"about_ca_topic_score_gemma":0.00005220007,"domain_scores_codex":[0.9970279,0.0003352551,0.0006871955,0.0006519126,0.0007223973,0.0005753647],"domain_scores_gemma":[0.9981181,0.0002603896,0.0002332406,0.0005061112,0.0007791347,0.000103045],"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":[0.0002878367,0.00004879595,0.00003602319,0.000586554,0.000004198316,0.000001233896,0.000662363,0.00008108022,0.9890296,0.0007257024,0.002285497,0.006251124],"study_design_scores_gemma":[0.0003081731,0.0002427389,0.0002703034,0.0002643456,0.000007918844,0.00000151787,0.0008976448,0.00172669,0.9903006,0.003017013,0.002777713,0.0001853667],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9916433,0.0001912545,0.002704123,0.00225355,0.0002913236,0.002237518,0.0002828047,0.0003732692,0.00002285106],"genre_scores_gemma":[0.9841368,0.0006639645,0.01260641,0.00004149158,0.0001331752,0.002185618,0.0001579511,0.00004405121,0.00003050779],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009902291,"threshold_uncertainty_score":0.6909162,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1181589064727593,"score_gpt":0.3703333051825091,"score_spread":0.2521743987097497,"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."}}