{"id":"W2918574956","doi":"10.1109/tmag.2019.2897669","title":"Evaluation of a Magnetic Dipole Model in a DC Magnetic Flux Leakage System","year":2019,"lang":"en","type":"article","venue":"IEEE Transactions on Magnetics","topic":"Non-Destructive Testing Techniques","field":"Engineering","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Dipole; Orientation (vector space); Magnetic field; Magnetic flux leakage; Magnetic dipole; Permeability (electromagnetism); Magnetic flux; Relative permeability; Algorithm; Physics; Materials science; Nuclear magnetic resonance; Computer science; Mathematical analysis; Geometry; Mathematics; Chemistry; Composite material; Quantum mechanics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0005036262,0.0005523539,0.0005900416,0.0005381536,0.0003117411,0.0009234493,0.0008136759,0.001115972,0.002437309],"category_scores_gemma":[0.001412188,0.0002817108,0.0004053708,0.0003298828,0.0005347588,0.0005789219,0.0004858873,0.0004199606,0.0005605393],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001027344,"about_ca_system_score_gemma":0.0008614003,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008153595,"about_ca_topic_score_gemma":0.003293014,"domain_scores_codex":[0.9997888,0.00005662133,0.000007063738,0.00003362243,0.00008937252,0.00002448289],"domain_scores_gemma":[0.9994677,0.0002286198,0.00005117087,0.00004926319,0.0001778369,0.00002542237],"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":[0.00009820789,0.00002543388,0.0007199062,0.00007224303,0.000008381348,0.0001118178,0.0000770855,0.9819751,0.00640111,0.004408884,0.0003485277,0.005753244],"study_design_scores_gemma":[0.000005831628,0.0000229719,0.000102515,0.000004824443,0.000003129506,0.00001620694,0.00001393833,0.9983967,0.0008359025,0.0002382601,0.0003565752,0.000003162927],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2611171,0.000682665,0.6876956,0.0004646553,0.0000780923,0.0002414334,0.0004461627,0.001849789,0.04742459],"genre_scores_gemma":[0.9686646,0.0002413664,0.02383278,0.00005254341,0.00001562655,0.0001001149,0.0001344964,0.0001179761,0.006840589],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008153595,"threshold_uncertainty_score":0.01621228,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02176210795830367,"score_gpt":0.2427976604655635,"score_spread":0.2210355525072598,"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."}}