{"id":"W2040765167","doi":"10.1115/1.3142871","title":"Automated Operating Mode Classification for Online Monitoring Systems","year":2009,"lang":"en","type":"article","venue":"Journal of vibration and acoustics","topic":"Machine Fault Diagnosis Techniques","field":"Engineering","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University; University of Alberta; Laurentian University","funders":"Natural Sciences and Engineering Research Council of Canada; Syncrude","keywords":"Excavator; Vibration; Condition monitoring; Mode (computer interface); Transient (computer programming); Fault detection and isolation; Fault (geology); Control engineering; Swing; Engineering; Computer science; Task (project management); Artificial intelligence; Actuator; Mechanical engineering","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0007596995,0.0005721249,0.0005609061,0.0009785029,0.0003813639,0.0006690074,0.0008436759,0.0007021386,0.002906999],"category_scores_gemma":[0.003815969,0.0002199798,0.000202584,0.0003685028,0.0003455771,0.001001088,0.0004181193,0.0006998986,0.001247019],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003301279,"about_ca_system_score_gemma":0.0004112974,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001078715,"about_ca_topic_score_gemma":0.001376244,"domain_scores_codex":[0.9991671,0.0002031989,0.00005107052,0.0001550555,0.0003582344,0.0000653511],"domain_scores_gemma":[0.9974819,0.001200693,0.0003136571,0.0004726723,0.0004840524,0.00004699254],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003794871,0.000163915,0.001600461,0.00009585159,0.00001816713,0.0001036735,0.0001225413,0.02215485,0.08736127,0.00291603,0.003477564,0.8816061],"study_design_scores_gemma":[0.00006693883,0.0003031098,0.004454523,0.00003240258,0.00002403149,0.000398444,0.00005337226,0.9035155,0.07366357,0.006405994,0.01102641,0.00005581184],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02397242,0.0002467433,0.968852,0.0001076772,0.00004653072,0.00008577226,0.00008702274,0.005339225,0.0012627],"genre_scores_gemma":[0.4807357,0.0001435446,0.5157654,0.00009409708,0.00008361724,0.0001751497,0.0002503182,0.0001347567,0.002617451],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002906999,"threshold_uncertainty_score":0.009724915,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02297605642995666,"score_gpt":0.3347669203561693,"score_spread":0.3117908639262127,"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."}}