{"id":"W2884449299","doi":"","title":"A new level set - finite element formulation for anisotropic grain growth","year":2018,"lang":"en","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Microstructure and mechanical properties","field":"Materials Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Safran Electronics (Canada)","funders":"","keywords":"Misorientation; Grain boundary; Grain growth; Materials science; Grain boundary strengthening; Anisotropy; Microstructure; Grain boundary diffusion coefficient; Boundary (topology); Surface energy; Stress (linguistics); Condensed matter physics; Geometry; Crystallography; Thermodynamics; Metallurgy; Mathematical analysis; Mathematics; Composite material; Physics; Chemistry; Optics","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.003146021,0.0003505994,0.0003752423,0.0001164553,0.0003904346,0.0004474196,0.001080743,0.000303344,0.0006025663],"category_scores_gemma":[0.001601114,0.0003246295,0.0002074191,0.0001378689,0.00008272734,0.0001359411,0.001133426,0.000256264,0.00008371798],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001230026,"about_ca_system_score_gemma":0.0004009718,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001233391,"about_ca_topic_score_gemma":0.001418788,"domain_scores_codex":[0.9964495,0.001328349,0.0005976483,0.0008155328,0.0003666407,0.0004423085],"domain_scores_gemma":[0.9957484,0.0004820499,0.0004940022,0.001355121,0.001722167,0.0001982721],"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":[0.0002036303,0.0003148249,0.000267038,0.0009385854,0.0001187146,0.000002042849,0.01470865,0.00008489985,0.6273259,0.2689459,0.05873964,0.02835022],"study_design_scores_gemma":[0.0009674234,0.000003486041,0.0003466259,0.0008633155,0.00007215155,0.000003745102,0.00005446291,0.006477423,0.8746882,0.07472899,0.0412411,0.0005530865],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0575234,0.0003626996,0.9329101,0.004286014,0.0007392644,0.001115087,0.0004699124,0.0002197243,0.00237384],"genre_scores_gemma":[0.7139283,0.0001384234,0.2696436,0.0003166843,0.0001774016,0.0001369539,0.001166396,0.00006866669,0.01442358],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6632665,"threshold_uncertainty_score":0.9999205,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03592874460069988,"score_gpt":0.2530910640436391,"score_spread":0.2171623194429392,"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."}}