{"id":"W4299431394","doi":"","title":"Direct computation of current density to solve 3D electric conduction problems using facet elements with FEM","year":2013,"lang":"en","type":"article","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":"Facet (psychology); Finite element method; Computation; Current density; Current (fluid); Thermal conduction; Computer science; Electrical engineering; Materials science; Physics; Algorithm; Engineering; Structural 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000313795,0.0004294644,0.0006002471,0.0004203041,0.0003784446,0.0007955487,0.00085215,0.0008612395,0.005545098],"category_scores_gemma":[0.001828449,0.0004512648,0.0005092929,0.0004092667,0.0004729808,0.000695892,0.0006959328,0.0008184297,0.0007984986],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000449078,"about_ca_system_score_gemma":0.0008144978,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003528632,"about_ca_topic_score_gemma":0.006264017,"domain_scores_codex":[0.9998549,0.00002455157,0.000005776815,0.00001284424,0.0000855824,0.00001634793],"domain_scores_gemma":[0.9993486,0.0003883596,0.00003584637,0.00006003589,0.0001368928,0.00003033388],"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":[0.0001314206,0.0001738849,0.001955052,0.0004368718,0.0000753217,0.0002899693,0.000430272,0.8252962,0.02633017,0.06498392,0.003633419,0.07626359],"study_design_scores_gemma":[0.000008171707,0.00001126512,0.00009577289,0.000006470064,0.000002801769,0.00003469461,0.0000217145,0.9949333,0.001330159,0.002637269,0.0009151372,0.000003275862],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.04840644,0.0001420025,0.9282191,0.000145906,0.00007926692,0.00008621114,0.0001347107,0.0006720084,0.02211445],"genre_scores_gemma":[0.5480695,0.0001969471,0.4404989,0.0001223772,0.00005747143,0.0002296386,0.0002287145,0.0004750894,0.01012129],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.005545098,"threshold_uncertainty_score":0.01855022,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02367261716427816,"score_gpt":0.2589487116268268,"score_spread":0.2352760944625486,"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."}}