{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004352024,0.0005261023,0.0004859437,0.000545857,0.0003730809,0.0007223241,0.001117461,0.001009225,0.00697358],"category_scores_gemma":[0.0008842086,0.0004074556,0.0005270206,0.0006087915,0.0003429207,0.0008628593,0.0007688411,0.000798594,0.001977882],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002921662,"about_ca_system_score_gemma":0.0007431683,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001297616,"about_ca_topic_score_gemma":0.002760111,"domain_scores_codex":[0.9998279,0.00003128442,0.00001031585,0.00001975665,0.0001000793,0.0000105764],"domain_scores_gemma":[0.9996657,0.00009416135,0.00002341379,0.00004561038,0.0001422558,0.00002884404],"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":[0.0001897781,0.0002273156,0.001173404,0.0003546873,0.00008214646,0.0002312698,0.0002409433,0.5519589,0.08069359,0.08473588,0.008641099,0.2714709],"study_design_scores_gemma":[0.000009584525,0.00001782998,0.00006970281,0.000006391536,0.000005440663,0.00003273055,0.000008367253,0.9890485,0.002480519,0.003367472,0.004943952,0.000009540106],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.004062553,0.00004148045,0.9922369,0.00004815241,0.00007477184,0.00002681241,0.00006380558,0.0004543152,0.002991316],"genre_scores_gemma":[0.09347875,0.0001526508,0.8967445,0.0001615737,0.00005606312,0.0001778218,0.0002773284,0.0006027988,0.008348507],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.00697358,"threshold_uncertainty_score":0.02332902,"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."}}