{"id":"W3136793860","doi":"10.18280/ejee.230103","title":"Harmonic Detection System and Identification Algorithm for Steel Pipeline Defects","year":2021,"lang":"en","type":"article","venue":"European Journal of Electrical Engineering","topic":"Non-Destructive Testing Techniques","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Key Research and Development Program of China","keywords":"Gate array; Field-programmable gate array; Hilbert–Huang transform; Pipeline (software); Harmonic; SIGNAL (programming language); Electronic engineering; Algorithm; ARM architecture; Computer science; Global Positioning System; Engineering; Acoustics; Computer hardware; Electrical engineering; Physics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003067805,0.0004015446,0.0004112328,0.0006820273,0.0002891107,0.000343738,0.0005450979,0.0005801664,0.001766034],"category_scores_gemma":[0.0006165689,0.000233834,0.0002986305,0.0003710823,0.000205609,0.0006138778,0.0003824851,0.0004064613,0.0005506733],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003078734,"about_ca_system_score_gemma":0.0005546316,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001560134,"about_ca_topic_score_gemma":0.001045951,"domain_scores_codex":[0.9997491,0.0000284992,0.00001424671,0.00007770638,0.000106425,0.00002387931],"domain_scores_gemma":[0.999788,0.00004250609,0.00002686021,0.00001929099,0.0001102835,0.00001322727],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002878514,0.00008393235,0.003034992,0.0002129261,0.00004391691,0.0001648769,0.0002405745,0.05202243,0.1656534,0.004972439,0.003125875,0.7701568],"study_design_scores_gemma":[0.00004909378,0.0002115463,0.002568815,0.00001103158,0.00003476079,0.0003960459,0.00005628066,0.9447323,0.04670355,0.001422618,0.003777152,0.0000366746],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02145861,0.0001036009,0.9764846,0.00005830766,0.00002401663,0.00003618382,0.00002408455,0.000854976,0.0009555299],"genre_scores_gemma":[0.4855763,0.0002566228,0.507461,0.00009807532,0.00005534089,0.0001528359,0.0001933787,0.00008201849,0.006124288],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001766034,"threshold_uncertainty_score":0.005907953,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009666819254083293,"score_gpt":0.2037321180919414,"score_spread":0.1940652988378581,"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."}}