{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000562218,0.0005290925,0.0007434071,0.0006010752,0.0003839653,0.001311436,0.00177613,0.002065596,0.004767573],"category_scores_gemma":[0.001327157,0.0006010489,0.000746935,0.00065151,0.0007283335,0.001004999,0.001282721,0.001666675,0.0009205698],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006369769,"about_ca_system_score_gemma":0.0009868423,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002658364,"about_ca_topic_score_gemma":0.004615612,"domain_scores_codex":[0.9997393,0.00005735875,0.00001525289,0.00003041597,0.0001389143,0.00001868463],"domain_scores_gemma":[0.9996566,0.000130601,0.00002953288,0.00004132764,0.0001048148,0.00003714555],"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":[0.00005720599,0.00009738615,0.0004356925,0.0001838822,0.00004716271,0.0001324145,0.00009746187,0.8230526,0.012442,0.1231676,0.003353474,0.03693304],"study_design_scores_gemma":[0.000005525942,0.000005561284,0.0000256742,0.000004207966,0.000002825264,0.00001259346,0.000004609191,0.9931555,0.0003490522,0.004713906,0.001717226,0.000003228067],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.005351644,0.0001138579,0.9879624,0.0002447925,0.0001108677,0.00004485133,0.0001144989,0.0001264422,0.005930603],"genre_scores_gemma":[0.1671964,0.0004388665,0.8128728,0.0004312161,0.0001460533,0.000376061,0.0004800005,0.0006707658,0.01738793],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004767573,"threshold_uncertainty_score":0.01594907,"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."}}