{"id":"W2277174252","doi":"10.1109/tmag.2015.2480960","title":"Numerical Impact of Using Different $E$ –$J$ Relationships for 3-D Simulations of AC Losses in MgB2Superconducting Wires","year":2015,"lang":"en","type":"article","venue":"IEEE Transactions on Magnetics","topic":"Superconductivity in MgB2 and Alloys","field":"Physics and Astronomy","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Nonlinear system; Eddy current; Superconductivity; Physics; Finite element method; Percolation (cognitive psychology); Current (fluid); Convergence (economics); Computation; Magnetic field; Relaxation (psychology); Mechanics; Field (mathematics); Statistical physics; Condensed matter physics; Computer science; Mathematics; Quantum mechanics; Thermodynamics","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":[0.0007318548,0.0006309887,0.0005211689,0.0004922373,0.0007546357,0.001226944,0.001011685,0.001603471,0.001811902],"category_scores_gemma":[0.002754726,0.0003687,0.0005977329,0.0006351652,0.000808022,0.0007366433,0.0006065467,0.0007910926,0.0002265616],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007563885,"about_ca_system_score_gemma":0.0008332728,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01360446,"about_ca_topic_score_gemma":0.009419523,"domain_scores_codex":[0.9997326,0.0001068239,0.00001853055,0.00002529224,0.00006916917,0.00004770705],"domain_scores_gemma":[0.9984878,0.001047872,0.0001344426,0.0001052469,0.0001489819,0.00007566262],"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":[0.0001539156,0.0001335503,0.002367394,0.00006505354,0.0000261601,0.0001249798,0.0001155842,0.9849415,0.005071304,0.002318841,0.000235144,0.004446616],"study_design_scores_gemma":[0.00001577885,0.00003835543,0.0002773539,0.000008020987,0.0000055896,0.00001297678,0.00003393245,0.9976538,0.00154994,0.0002184886,0.0001776652,0.000008153533],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.929967,0.0004957066,0.05104961,0.0006531951,0.00009187721,0.0001050333,0.0004019133,0.0006419225,0.01659369],"genre_scores_gemma":[0.9765244,0.0001921582,0.02167512,0.0000924424,0.00001212951,0.00007700808,0.0001325303,0.0001242513,0.001169873],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01360446,"threshold_uncertainty_score":0.02705055,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1319659185082317,"score_gpt":0.3466666871134993,"score_spread":0.2147007686052675,"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."}}