{"id":"W1978044728","doi":"10.1109/demped.2009.5292792","title":"A new strategy for condition monitoring of adjustable speed induction machine drive systems","year":2009,"lang":"en","type":"article","venue":"","topic":"Machine Fault Diagnosis Techniques","field":"Engineering","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"","keywords":"Stator; Rotor (electric); Inverter; Induction motor; Adjustable-speed drive; Line (geometry); Fault (geology); Computer science; Component (thermodynamics); Condition monitoring; Automotive engineering; Engineering; Reliability engineering; Voltage; Electrical 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008543085,0.0001258535,0.0001923334,0.0001164939,0.00002126817,0.00002662451,0.0000797485,0.0000878665,0.00003473219],"category_scores_gemma":[0.00001528207,0.0001239768,0.00004455231,0.0001236981,0.000004603265,0.000217214,0.000004667868,0.00008849542,0.000002292314],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000702918,"about_ca_system_score_gemma":0.00001245585,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003830163,"about_ca_topic_score_gemma":0.000006928351,"domain_scores_codex":[0.9993606,0.000008923288,0.000249896,0.0001158814,0.0001052131,0.0001594561],"domain_scores_gemma":[0.9996676,0.00003125844,0.00004680755,0.0001425472,0.00005546945,0.0000563364],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00006462048,0.0002084512,0.006408824,0.0009258278,0.0001954204,0.000004856089,0.0003825903,0.3072156,0.4788487,0.03207321,0.06568045,0.1079915],"study_design_scores_gemma":[0.0009630127,0.000566347,0.01247842,0.000242136,0.00006204372,0.00001145392,0.0002453993,0.1351164,0.8451091,0.003405218,0.001382486,0.0004179533],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6109564,0.001204893,0.3666975,0.0001117168,0.001033679,0.001948578,0.00006691241,0.002508417,0.01547194],"genre_scores_gemma":[0.9921838,0.00005513952,0.007147889,0.000003757608,0.0002446185,0.00002015502,0.00003268851,0.00001968915,0.0002922571],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3812274,"threshold_uncertainty_score":0.5055627,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02111942780237467,"score_gpt":0.3050225782119015,"score_spread":0.2839031504095268,"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."}}