{"id":"W3183704026","doi":"","title":"A new 3D scalar finite element method to compute T0","year":2005,"lang":"en","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Electromagnetic Simulation and Numerical Methods","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Center for Diagnosis and Research on Alzheimer's Disease","funders":"","keywords":"Decoupling (probability); Finite element method; Conductor; Scalar (mathematics); Magnetic potential; Magnetic field; Scalar potential; Computer science; Vector potential; Mixed finite element method; Current density; Mathematical analysis; Physics; Applied mathematics; Mathematics; Classical mechanics; Geometry; Engineering; Control engineering","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":[0.003354225,0.0004313003,0.0005111963,0.0002705428,0.0001380639,0.000267396,0.000992996,0.0002877248,0.0006554034],"category_scores_gemma":[0.0006746502,0.000491022,0.0002104001,0.0005618435,0.0000356523,0.00006441644,0.0007822022,0.0007519925,0.0001493325],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001987515,"about_ca_system_score_gemma":0.00014194,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002954832,"about_ca_topic_score_gemma":0.0002291989,"domain_scores_codex":[0.9943271,0.003393555,0.000661506,0.0006787781,0.0004412878,0.000497744],"domain_scores_gemma":[0.9949595,0.002143563,0.0001654505,0.00159236,0.000657628,0.0004814724],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000008022314,0.0001216829,0.00008203222,0.00009489545,0.00009900855,0.000002780266,0.002613219,0.105301,0.002730298,0.006064578,0.004491848,0.8783906],"study_design_scores_gemma":[0.0004996734,0.000001198625,0.001235303,0.0006372327,0.00005785119,0.000005470275,0.00001129489,0.7875171,0.02924083,0.001985509,0.1781729,0.0006356097],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001480432,0.0009527723,0.9517692,0.00642745,0.0002895436,0.0005259783,0.00001997213,0.0006722882,0.03786241],"genre_scores_gemma":[0.02911505,0.0002157486,0.9632306,0.000311133,0.0000983793,0.00005933963,0.0001411032,0.00008837057,0.006740323],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.877755,"threshold_uncertainty_score":0.9997541,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01429896104330055,"score_gpt":0.267886285682681,"score_spread":0.2535873246393804,"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."}}