{"id":"W4255542815","doi":"10.1109/tmag.2006.880088","title":"Multiquadrics Collocation Method for Transient Eddy Current Problems","year":2006,"lang":"en","type":"article","venue":"IEEE Transactions on Magnetics","topic":"Magnetic Properties and Applications","field":"Materials Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Eddy current; Transient (computer programming); Discretization; Current (fluid); Collocation (remote sensing); Computer science; Applied mathematics; Mechanics; Mathematical analysis; Mathematics; Physics","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":[0.0002616071,0.0001940875,0.0001773567,0.0000872969,0.0003244566,0.00008407416,0.0002112548,0.00008276849,0.0003883939],"category_scores_gemma":[0.000004249908,0.0001778379,0.0001108811,0.000232142,0.0000747814,0.00006661339,0.000001060647,0.0001244906,0.00009403049],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005870495,"about_ca_system_score_gemma":0.00006271216,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001690171,"about_ca_topic_score_gemma":0.0001864019,"domain_scores_codex":[0.9985609,0.00005635126,0.0004174969,0.0003877941,0.0002528121,0.0003246144],"domain_scores_gemma":[0.9991714,0.0001269943,0.00008762342,0.0003518198,0.0001815419,0.0000805836],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00007006283,0.001243696,0.000001218098,0.0001764093,0.000005371048,2.423794e-7,0.0003214256,0.1653481,0.6182234,0.001451301,0.003061061,0.2100977],"study_design_scores_gemma":[0.001575428,0.0008534313,0.0001144331,0.00005659361,0.0001849657,0.000007476859,0.00009441286,0.1730535,0.5931214,0.001784061,0.2285783,0.0005759024],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00800858,0.0002638907,0.9881384,0.0007943256,0.0007404886,0.001331395,0.0002024103,0.0001445522,0.0003759171],"genre_scores_gemma":[0.7526179,0.0001636226,0.2412787,0.0001559868,0.0001940587,0.002013052,0.00002712882,0.00005607945,0.003493505],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7468597,"threshold_uncertainty_score":0.7252017,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02417877163571654,"score_gpt":0.2822102731225782,"score_spread":0.2580315014868617,"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."}}