{"id":"W2109952342","doi":"10.1109/tec.2015.2432763","title":"Hysteresis-Dependent Model for the Brushless Exciter of Synchronous Generators","year":2015,"lang":"en","type":"article","venue":"IEEE Transactions on Energy Conversion","topic":"Magnetic Properties and Applications","field":"Materials Science","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Exciter; Armature (electrical engineering); Control theory (sociology); Flux linkage; Hysteresis; Synchronous motor; DC motor; Magnetic flux; Excited state; Generator (circuit theory); Magnetization; Magnetic field; Physics; Computer science; Engineering; Magnet; Electrical engineering; Voltage; Acoustics; Induction motor; Direct torque control; Condensed matter physics","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":[],"consensus_categories":[],"category_scores_codex":[0.0001519563,0.0001066565,0.0001215852,0.00004343125,0.0001828957,0.00002498015,0.0002483929,0.00005844029,0.0001980718],"category_scores_gemma":[0.000001992383,0.00007233259,0.00007511533,0.0000668279,0.00008422831,0.00007922661,0.000003015953,0.00004166708,0.00002752461],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005057175,"about_ca_system_score_gemma":0.00008581903,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003561524,"about_ca_topic_score_gemma":0.00007045502,"domain_scores_codex":[0.999213,0.00002967403,0.0001943638,0.0002040147,0.0002031113,0.0001558241],"domain_scores_gemma":[0.9993272,0.00006513497,0.00006910694,0.0003416539,0.0001180351,0.00007887124],"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":[0.000346095,0.0003164729,0.000001262578,0.00004912494,0.00003117614,6.276072e-7,0.0007992669,0.4803946,0.495703,0.001220297,0.003152614,0.01798551],"study_design_scores_gemma":[0.0005127602,0.0001090088,0.000001214662,0.00001057331,0.0000426779,0.000001798333,0.0001672623,0.3428729,0.654087,0.0001263881,0.001972209,0.00009619026],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0976784,0.00009667293,0.9010284,0.0003354057,0.0004435985,0.000162096,0.00005626362,0.00003356149,0.0001656207],"genre_scores_gemma":[0.9958703,0.00004618783,0.001249722,0.0002238575,0.00003497102,0.0001423658,0.000001969063,0.00001413732,0.002416484],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8997787,"threshold_uncertainty_score":0.2949637,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03431541392421136,"score_gpt":0.2322541765867161,"score_spread":0.1979387626625047,"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."}}