{"id":"W2589068190","doi":"10.1063/1.4974681","title":"Comparison of analytical eddy current models using principal components analysis","year":2017,"lang":"en","type":"article","venue":"AIP conference proceedings","topic":"Non-Destructive Testing Techniques","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Royal Military College of Canada; Queen's University","funders":"University Network of Excellence in Nuclear Engineering","keywords":"Eddy current; Eddy-current testing; Electromagnetic coil; Coaxial; Offset (computer science); Acoustics; Mechanics; Principal component analysis; Electronic engineering; Materials science; Engineering; Mathematics; Electrical engineering; Physics; Computer science; Statistics","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":[0.002107797,0.001640175,0.0007385848,0.002131658,0.0005397106,0.001425156,0.0009762122,0.0007290638,0.002654415],"category_scores_gemma":[0.006502057,0.0004542548,0.001225193,0.001499414,0.0004304311,0.001367035,0.0004774807,0.0007914893,0.001081152],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008567141,"about_ca_system_score_gemma":0.001439117,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01020592,"about_ca_topic_score_gemma":0.005536994,"domain_scores_codex":[0.9991948,0.0002556287,0.00006350152,0.0001479897,0.0002787015,0.00005936767],"domain_scores_gemma":[0.9977744,0.001204854,0.0001514811,0.0001954566,0.0006329698,0.00004065623],"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":[0.0002708977,0.0002871896,0.002285531,0.0003270544,0.000150054,0.00009995239,0.0003286295,0.8275747,0.005908551,0.007401742,0.002305102,0.1530606],"study_design_scores_gemma":[0.00001238118,0.00004803169,0.0008358764,0.00001181878,0.00001442441,0.00002496801,0.00005502393,0.9949875,0.001285472,0.001744392,0.0009551595,0.00002496394],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1162299,0.0004468454,0.8747063,0.0001856391,0.00009298597,0.0003203077,0.0004754558,0.003012948,0.004529593],"genre_scores_gemma":[0.7150155,0.0007946566,0.2781213,0.00005152096,0.00004117296,0.0007347456,0.001547884,0.0005548346,0.003138384],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01020592,"threshold_uncertainty_score":0.02029306,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1670131953514845,"score_gpt":0.3764653842019571,"score_spread":0.2094521888504726,"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."}}