{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000570367,0.0001361477,0.0001938172,0.0001765999,0.00003887415,0.00006080035,0.00009925193,0.00002907694,7.420616e-7],"category_scores_gemma":[0.0003168107,0.0001446781,0.00007646313,0.0003000828,0.000007379171,0.0001359782,0.00001746354,0.0002806038,0.000001825689],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001608137,"about_ca_system_score_gemma":0.00001490082,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":1.896282e-7,"about_ca_topic_score_gemma":8.61145e-8,"domain_scores_codex":[0.9990746,0.0000563802,0.0004274367,0.0001193713,0.0001272496,0.0001949648],"domain_scores_gemma":[0.9993545,0.0001369548,0.00009810766,0.0001052072,0.0002099297,0.00009525793],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000005908747,0.00001198317,0.00001456671,0.0001650305,0.00005071692,0.0001263952,0.00002674,0.002081157,0.885187,0.0003924983,0.00007934708,0.1118586],"study_design_scores_gemma":[0.0006795154,0.0002221815,0.003225133,0.0002487299,0.00009660325,0.001868225,0.00001595514,0.6056122,0.3870821,0.0002181295,0.0004297064,0.0003015834],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0763428,0.001363371,0.9214126,0.000005841807,0.0002819186,0.00008389477,0.00000195752,0.0003273874,0.0001802197],"genre_scores_gemma":[0.7421417,0.00004859867,0.2575182,0.000002818467,0.0002228485,0.00000259798,0.000001133953,0.0000569556,0.000005172312],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6657989,"threshold_uncertainty_score":0.5899801,"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."}}