{"id":"W4312729682","doi":"10.1109/pesgm48719.2022.9917225","title":"Induction Machine Emulation for Extreme Weather Conditions","year":2022,"lang":"en","type":"article","venue":"2022 IEEE Power & Energy Society General Meeting (PESGM)","topic":"Real-time simulation and control systems","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Emulation; Robustness (evolution); Voltage; Computer science; Electric power system; Hardware-in-the-loop simulation; Engineering; Control engineering; Power (physics); Electrical 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0006048725,0.0003169942,0.0003284814,0.0001009381,0.0007853507,0.00008996936,0.0002056111,0.000146041,0.001190511],"category_scores_gemma":[0.00002638005,0.0003596812,0.0004644602,0.0003993215,0.00003084557,0.0001950157,0.00004914791,0.0002824404,0.00002301821],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003592315,"about_ca_system_score_gemma":0.00003232409,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000254237,"about_ca_topic_score_gemma":0.0001152589,"domain_scores_codex":[0.9979202,0.0001831142,0.0005513485,0.0004202937,0.0004629508,0.0004620594],"domain_scores_gemma":[0.9991306,0.0001075084,0.0001625711,0.0003807555,0.00009822918,0.000120346],"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":[0.00001613429,0.0000430299,0.0001403532,0.0000187677,0.0001821952,3.795241e-7,0.0008924499,0.8109251,0.1348436,0.0006663992,0.05140227,0.0008693628],"study_design_scores_gemma":[0.001137265,0.00004348707,0.0001490887,0.00001354944,0.0000601016,0.00001214982,0.0003096648,0.5249622,0.0006640053,0.0005100939,0.4716446,0.0004937199],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7011234,0.003107282,0.2579504,0.001235221,0.01560279,0.001370558,0.0006971326,0.002351115,0.01656215],"genre_scores_gemma":[0.9794249,0.00003784395,0.002501173,0.0004297213,0.0008786808,0.000584776,0.0009145139,0.0001369104,0.01509149],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4202424,"threshold_uncertainty_score":0.9998855,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02376145176440185,"score_gpt":0.2429133267349428,"score_spread":0.219151874970541,"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."}}