{"id":"W2944329638","doi":"10.1109/iicpe.2018.8709445","title":"Challenges in Developing Hardware-In-Loop Model of Cage Induction Motor with Eccentricity Fault","year":2018,"lang":"en","type":"article","venue":"","topic":"Real-time simulation and control systems","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"","keywords":"MATLAB; Induction motor; Eccentricity (behavior); Fault model; Computer science; Fault (geology); Control engineering; Electric motor; Control theory (sociology); Simulation; Engineering; Voltage; Control (management); Electronic circuit; Artificial intelligence; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000244727,0.0003799227,0.0005114234,0.0001666876,0.000258338,0.0006588802,0.0009973695,0.0006082023,0.002570523],"category_scores_gemma":[0.0005948038,0.0002205107,0.0004331099,0.0001002121,0.000267195,0.0006299051,0.0002493573,0.0006260155,0.0008375819],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003146332,"about_ca_system_score_gemma":0.0006585229,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003212654,"about_ca_topic_score_gemma":0.00311119,"domain_scores_codex":[0.999846,0.00004359363,0.00001044618,0.00002099808,0.00006480829,0.00001411383],"domain_scores_gemma":[0.9997074,0.0001129021,0.00004260193,0.00004237316,0.00008457931,0.00001017227],"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":[0.00007396114,0.00005091693,0.001103002,0.0002484951,0.00002730441,0.0002852651,0.0001783466,0.9445487,0.01759947,0.008270266,0.0006674349,0.02694673],"study_design_scores_gemma":[0.00001067663,0.00009368185,0.0002436513,0.00001451771,0.00001044163,0.0001145967,0.00002605854,0.9907233,0.004089737,0.0008002995,0.00386724,0.00000578608],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03480139,0.0002199439,0.9536793,0.0002031592,0.00005418934,0.000107369,0.0001155324,0.001541911,0.009277226],"genre_scores_gemma":[0.8429934,0.0005258784,0.1448233,0.00009313605,0.00002774086,0.0002684333,0.0002305733,0.000234152,0.0108034],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003212654,"threshold_uncertainty_score":0.008599222,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05023730315090571,"score_gpt":0.2464274047034722,"score_spread":0.1961901015525665,"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."}}