{"id":"W4250868376","doi":"10.32920/ryerson.14648091","title":"Intelligent Condition Monitoring Models For Rotating","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Machine Fault Diagnosis Techniques","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Downtime; Condition monitoring; Computer science; Condition-based maintenance; Vibration; Noise (video); Fuzzy logic; Bayesian probability; Function (biology); Artificial intelligence; Machine learning; Reliability engineering; Engineering","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":[0.0008952603,0.0008037791,0.000832768,0.0008562327,0.0003909731,0.001125835,0.00146692,0.001356851,0.004232576],"category_scores_gemma":[0.003117468,0.0004362366,0.0009419368,0.0005310437,0.0005951157,0.001222388,0.0005429984,0.0009989823,0.0008625173],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001283121,"about_ca_system_score_gemma":0.0009698152,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009761975,"about_ca_topic_score_gemma":0.006341908,"domain_scores_codex":[0.9994937,0.00008661708,0.00002571871,0.0001578175,0.0001749605,0.00006115098],"domain_scores_gemma":[0.9991986,0.0003558794,0.0001641309,0.00004526225,0.0002080547,0.00002806374],"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":[0.00005474988,0.00003100885,0.0006178576,0.00003570438,0.00001754767,0.00004937727,0.00006055752,0.9634745,0.001407866,0.01702031,0.0006467573,0.01658383],"study_design_scores_gemma":[0.000002811638,0.000006807284,0.0001043408,0.000002458884,0.000004162523,0.000008478954,0.000001636884,0.9971896,0.0001725378,0.002252957,0.0002509156,0.000003314828],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01502406,0.0002188805,0.9792978,0.0001841049,0.00003271757,0.00004917647,0.0002063209,0.0006062615,0.004380826],"genre_scores_gemma":[0.8382913,0.0006405219,0.1472497,0.0001179361,0.00006513437,0.0003956211,0.0006915915,0.0001236971,0.01242462],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009761975,"threshold_uncertainty_score":0.01941031,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03810378468685059,"score_gpt":0.3383385042103353,"score_spread":0.3002347195234847,"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."}}