{"id":"W2101845616","doi":"10.1109/20.951317","title":"Improved finite element method for EMAT analysis and design","year":2001,"lang":"en","type":"article","venue":"IEEE Transactions on Magnetics","topic":"Non-Destructive Testing Techniques","field":"Engineering","cited_by":49,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Electromagnetic acoustic transducer; Finite element method; Electrical conductor; Acoustics; Transducer; Lift (data mining); Materials science; Computer science; Physics; Ultrasonic sensor; Composite material","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":[0.0006344516,0.0007883083,0.0007385714,0.0006643928,0.0003001398,0.0005065459,0.001273259,0.001109723,0.01068367],"category_scores_gemma":[0.00133112,0.0004384487,0.0006883623,0.0005817513,0.0002933994,0.0006690963,0.0005525758,0.001266955,0.004763317],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003193138,"about_ca_system_score_gemma":0.000616353,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001207571,"about_ca_topic_score_gemma":0.002038373,"domain_scores_codex":[0.9995986,0.0001091423,0.00001707738,0.00002733083,0.0002301148,0.00001786776],"domain_scores_gemma":[0.9995052,0.000229486,0.00002753122,0.00005920708,0.0001655734,0.00001305191],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00008925558,0.00009370941,0.0004546887,0.000431309,0.00009842077,0.0001346889,0.0001170627,0.570755,0.04027854,0.04821069,0.01027836,0.3290583],"study_design_scores_gemma":[0.00001487685,0.0000297813,0.00009007638,0.00002566178,0.00001323437,0.00008545601,0.00001106084,0.9688204,0.003471074,0.004602872,0.02282289,0.00001266857],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0005234362,0.00008467657,0.9973831,0.00002637947,0.00002089771,0.00002080447,0.00003040941,0.0003784251,0.001531816],"genre_scores_gemma":[0.02925163,0.0002827027,0.9638293,0.00007483679,0.00002424327,0.0003741873,0.0002214218,0.0002736518,0.005668118],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01068367,"threshold_uncertainty_score":0.03574049,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02588662588677042,"score_gpt":0.2783005374147859,"score_spread":0.2524139115280155,"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."}}