{"id":"W4300812859","doi":"","title":"2D Integral Formulations for Nonlinear Magneto-static Field Computation and Rotating Machines Pre-Design","year":2016,"lang":"en","type":"article","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Electromagnetic Scattering and Analysis","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Center for Diagnosis and Research on Alzheimer's Disease","funders":"","keywords":"Nonlinear system; Computation; Magneto; Magnetostatics; Field (mathematics); Computer science; Magnetic field; Physics; Mechanical engineering; Mathematics; Engineering; Algorithm; Magnet","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":[],"consensus_categories":[],"category_scores_codex":[0.0008263752,0.0001162891,0.0001339356,0.00006622708,0.0002391243,0.0001116796,0.0001465099,0.00002752361,0.000100444],"category_scores_gemma":[0.0002148937,0.00009277397,0.00007146903,0.000132391,0.00004531499,0.0001131903,0.00005284405,0.00006329002,0.000004684131],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001022949,"about_ca_system_score_gemma":0.00003260667,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003384927,"about_ca_topic_score_gemma":0.00007967887,"domain_scores_codex":[0.9987819,0.0004899345,0.0002254381,0.0002351468,0.00009204646,0.0001755456],"domain_scores_gemma":[0.997044,0.002140888,0.0001350765,0.0002457961,0.0003722615,0.0000620131],"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":[0.00001490883,0.0001458236,0.01382021,0.00002838713,0.00006112627,1.529156e-7,0.002282164,0.000104475,0.01035129,0.0260015,0.0004733993,0.9467165],"study_design_scores_gemma":[0.00151938,0.000008572782,0.006263149,0.0005997224,0.0001164677,0.000002503284,0.0001362667,0.9078137,0.04477552,0.03731798,0.001038285,0.0004084631],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2157504,0.00003255925,0.7780456,0.004673361,0.00001597206,0.0001682169,0.000020217,0.0000386032,0.001255086],"genre_scores_gemma":[0.7672307,0.000005597435,0.2296473,0.00003614997,0.0000209206,0.00004507972,0.0000699641,0.00001319791,0.002931065],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9463081,"threshold_uncertainty_score":0.3783213,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009670672883449636,"score_gpt":0.240855901170275,"score_spread":0.2311852282868254,"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."}}