{"id":"W4285814011","doi":"10.1109/iwcmc55113.2022.9824540","title":"Sound Event Classification in an Industrial Environment: Pipe Leakage Detection Use Case","year":2022,"lang":"en","type":"article","venue":"2022 International Wireless Communications and Mobile Computing (IWCMC)","topic":"Water Systems and Optimization","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Support vector machine; Computer science; Pipeline (software); Pipeline transport; Generalizability theory; Noise (video); Data mining; Artificial intelligence; Curse of dimensionality; Feature selection; Machine learning; Pattern recognition (psychology); Engineering; Mathematics; Statistics","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0008543501,0.0008562657,0.0007830891,0.001054252,0.0004570952,0.0008302167,0.0009790401,0.00148458,0.001074789],"category_scores_gemma":[0.001872076,0.0002596227,0.0007551822,0.0008972662,0.0005241337,0.0009458903,0.0008045998,0.0005557948,0.0004680757],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005572676,"about_ca_system_score_gemma":0.00066806,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004731837,"about_ca_topic_score_gemma":0.005675812,"domain_scores_codex":[0.9991221,0.0001355036,0.00007850592,0.000243222,0.0002878219,0.0001328324],"domain_scores_gemma":[0.999216,0.0003457823,0.00008712472,0.0001062782,0.0001874162,0.00005753312],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.002330583,0.001790684,0.1901022,0.0009497571,0.0002646137,0.009383779,0.0007171939,0.3573779,0.06484653,0.002228487,0.007562108,0.362446],"study_design_scores_gemma":[0.00007599873,0.0005629589,0.04800072,0.00003774184,0.00009893801,0.001063346,0.0005156148,0.9051088,0.04043616,0.001405502,0.002636726,0.00005748071],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8643056,0.0003582324,0.1299477,0.0004961244,0.00007038893,0.0001613027,0.0009676942,0.00111959,0.002573403],"genre_scores_gemma":[0.9671008,0.000153177,0.03025931,0.0000634824,0.00002958003,0.00006954606,0.0008656827,0.00002505729,0.001433327],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004731837,"threshold_uncertainty_score":0.009408593,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04427978310220612,"score_gpt":0.2540184361707086,"score_spread":0.2097386530685025,"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."}}