{"id":"W2109869613","doi":"10.1109/20.908707","title":"Calculation improvement of 3D linear magnetostatic field based on fictitious magnetic surface charge","year":2000,"lang":"en","type":"article","venue":"IEEE Transactions on Magnetics","topic":"Non-Destructive Testing Techniques","field":"Engineering","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Polytechnique Montréal","funders":"","keywords":"Computation; Magnetic field; Magnetostatics; Surface (topology); Boundary value problem; Boundary (topology); Field (mathematics); Charge (physics); Physics; Mechanics; Computer science; Classical mechanics; Computational physics; Mathematical analysis; Mathematics; Algorithm; Geometry","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":[0.000239225,0.00031001,0.0004378552,0.0004741516,0.0002214337,0.0003988284,0.0007483079,0.0004629702,0.001569116],"category_scores_gemma":[0.0006233898,0.0001866063,0.0004838244,0.0002207113,0.0002639027,0.0008166684,0.0003909315,0.0003494108,0.0004043277],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003036417,"about_ca_system_score_gemma":0.0004521085,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009574627,"about_ca_topic_score_gemma":0.000893779,"domain_scores_codex":[0.9998626,0.00002216493,0.000005059839,0.00001089357,0.00008974768,0.000009559774],"domain_scores_gemma":[0.9998416,0.00006214382,0.00001092288,0.00002297839,0.00005347031,0.000008813103],"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":[0.00007345455,0.0000792945,0.001049635,0.0005196981,0.00006432583,0.0003704228,0.0003159747,0.5165198,0.09939466,0.1594802,0.003325438,0.218807],"study_design_scores_gemma":[0.0000100891,0.00002459203,0.0001491129,0.000007545616,0.00000633173,0.00009720381,0.00001060187,0.9827576,0.008049167,0.005678058,0.003200199,0.000009458908],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01254414,0.0001598799,0.9831074,0.0000643331,0.00004364434,0.00002509704,0.00002479228,0.0003734272,0.003657199],"genre_scores_gemma":[0.5308232,0.0004981974,0.4638391,0.00007413093,0.00005198357,0.0001588081,0.0001245472,0.0002075174,0.004222544],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001569116,"threshold_uncertainty_score":0.005249262,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008402423688091538,"score_gpt":0.2216815111895893,"score_spread":0.2132790875014977,"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."}}