{"id":"W2013714836","doi":"10.1109/ipec.2014.6870127","title":"Induction machine based flywheel speed estimation at stand-by mode","year":2014,"lang":"en","type":"article","venue":"","topic":"Sensorless Control of Electric Motors","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Flywheel; Flywheel energy storage; Rotor (electric); Mode (computer interface); Energy (signal processing); Control theory (sociology); Scheme (mathematics); Computer science; Engineering; Automotive engineering; Power (physics); Energy storage; Control (management); Mathematics; Artificial intelligence; Electrical engineering; Physics","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":[0.0001157259,0.0003906199,0.0003633652,0.0003276605,0.0002070805,0.0003114188,0.0004182286,0.0002474531,0.001055311],"category_scores_gemma":[0.000430912,0.0001475115,0.000107243,0.0001886515,0.0001231441,0.0004521408,0.000133976,0.0002897274,0.0003294531],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001709958,"about_ca_system_score_gemma":0.000271603,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001396912,"about_ca_topic_score_gemma":0.002432797,"domain_scores_codex":[0.9998678,0.00001488024,0.000008465449,0.00003396801,0.00006611344,0.000008707408],"domain_scores_gemma":[0.9998239,0.00004787143,0.00003770955,0.00002100667,0.00006245969,0.000007193082],"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":[0.0005228644,0.0001622139,0.004339262,0.0002817982,0.00005499867,0.0001547473,0.000165593,0.0382958,0.3227813,0.00247803,0.001459744,0.6293038],"study_design_scores_gemma":[0.00007186534,0.000493899,0.01087588,0.00003662519,0.00004937081,0.00043405,0.00005061878,0.8001761,0.1808454,0.001100498,0.005813008,0.00005253791],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1127814,0.0002968276,0.8827001,0.00005678078,0.00004427654,0.00006006955,0.00009561899,0.001685968,0.002278905],"genre_scores_gemma":[0.9237305,0.0001145845,0.07392225,0.00002425802,0.00001279298,0.00003256643,0.0001169357,0.00002739034,0.002018791],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001396912,"threshold_uncertainty_score":0.003530324,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005122652645585563,"score_gpt":0.1968800008508713,"score_spread":0.1917573482052857,"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."}}