{"id":"W2051296266","doi":"10.5539/mas.v2n6p148","title":"Artificial Neural Network Based Rotor Position Estimation for Switched Reluctance Motor","year":2008,"lang":"en","type":"article","venue":"Modern Applied Science","topic":"Electric Motor Design and Analysis","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Board of Research in Nuclear Sciences; Bhabha Atomic Research Centre","keywords":"Switched reluctance motor; Rotor (electric); Artificial neural network; Computer science; Position (finance); Position sensor; Software; Control theory (sociology); SIGNAL (programming language); Interface (matter); Digital signal processing; Control engineering; Artificial intelligence; Engineering; Computer hardware; Control (management); Electrical engineering","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002656323,0.0001340761,0.0001501108,0.000113675,0.000409535,0.00005129201,0.0002232055,0.00004978692,0.000007987591],"category_scores_gemma":[0.00001977845,0.0001374809,0.00005725972,0.0007152301,0.00009996656,0.0001587877,0.000008778031,0.00008885261,0.00001207683],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001223431,"about_ca_system_score_gemma":0.00005690819,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002471995,"about_ca_topic_score_gemma":0.000002018065,"domain_scores_codex":[0.998768,0.000006062055,0.0002088563,0.0002980119,0.0003193399,0.0003996695],"domain_scores_gemma":[0.9995545,0.00004635801,0.00004284813,0.0002122461,0.00005101346,0.00009299903],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002396449,0.0000110987,0.00001626983,0.000009170259,0.000003120317,9.612237e-7,0.00005401766,0.4059731,0.5765589,0.0003086528,0.0001206049,0.01692013],"study_design_scores_gemma":[0.0001190698,0.00002520532,0.0004127651,0.000004526906,0.00001096479,0.000002092813,9.126841e-7,0.9675941,0.02911782,0.002537266,0.00001940169,0.0001558923],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1319694,0.00003612433,0.8668725,0.00004413696,0.00009318435,0.0004205231,0.000003402996,0.0002385985,0.0003221759],"genre_scores_gemma":[0.9470806,0.000002042009,0.05241125,0.00009897244,0.0001501653,0.00019743,0.000009540181,0.0000185523,0.00003147831],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8151112,"threshold_uncertainty_score":0.5606308,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01728372133475481,"score_gpt":0.217933364361014,"score_spread":0.2006496430262592,"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."}}