{"id":"W2985992878","doi":"10.1108/jqme-10-2018-0087","title":"Fault detection for parallel operating machines","year":2019,"lang":"en","type":"article","venue":"Journal of Quality in Maintenance Engineering","topic":"Machine Fault Diagnosis Techniques","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Laurentian University","funders":"","keywords":"Redundancy (engineering); Fault detection and isolation; Residual; Computer science; Autoregressive model; Fault (geology); Condition monitoring; Vibration; Bearing (navigation); Reliability engineering; Real-time computing; Control engineering; Engineering; Algorithm; Artificial intelligence","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":[0.0004055759,0.000400486,0.000481258,0.001042516,0.0002118403,0.0003323288,0.0004114147,0.0003933019,0.001150239],"category_scores_gemma":[0.002549629,0.0001810587,0.0003126117,0.0004310739,0.0002999739,0.0005683927,0.0003745793,0.0003114622,0.0002494156],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003064998,"about_ca_system_score_gemma":0.0002452315,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001357225,"about_ca_topic_score_gemma":0.001179473,"domain_scores_codex":[0.9995494,0.00005580908,0.00002505055,0.0001124976,0.0002116439,0.00004557946],"domain_scores_gemma":[0.9988709,0.0004877348,0.0002786914,0.0001279433,0.0002036266,0.00003109877],"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":[0.0009815743,0.0002584459,0.02582874,0.0002512037,0.0001077577,0.0005744458,0.0002539318,0.1605146,0.1665101,0.001981785,0.0006893606,0.642048],"study_design_scores_gemma":[0.00002606346,0.0005762887,0.02373694,0.00001388535,0.00004113027,0.0006797115,0.00009588653,0.9352789,0.03595283,0.002550652,0.001024149,0.00002354561],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4784414,0.000282596,0.5190432,0.00006894057,0.00003645744,0.0000655995,0.00007613979,0.0009062824,0.001079281],"genre_scores_gemma":[0.965478,0.00005697884,0.03385597,0.000009128428,0.00001060678,0.00001408152,0.00005923709,0.00001427423,0.0005016802],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001357225,"threshold_uncertainty_score":0.003847957,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01262631600825131,"score_gpt":0.2997699237758784,"score_spread":0.2871436077676271,"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."}}