{"id":"W2129089228","doi":"10.1109/ppic.2012.6293007","title":"Using magnetic flux monitoring to detect synchronous machine rotor winding shorts","year":2012,"lang":"en","type":"article","venue":"","topic":"Non-Destructive Testing Techniques","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Power Generation","funders":"","keywords":"Stator; Rotor (electric); Engineering; Synchronous motor; Electromagnetic coil; Synchronizing; Electrical engineering; Vibration; Magnetic flux; Automotive engineering; Control theory (sociology); Computer science; Physics; Acoustics; Magnetic field; Topology (electrical circuits)","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002134115,0.000249671,0.00020065,0.000201087,0.00008766681,0.00004824159,0.0001796623,0.00008109491,0.0001648127],"category_scores_gemma":[0.00006791329,0.0002619146,0.00004591783,0.0002635293,0.00001753925,0.0002698344,0.0001024569,0.0001915687,0.00005386319],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003868162,"about_ca_system_score_gemma":0.000009269295,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009761783,"about_ca_topic_score_gemma":0.00000354847,"domain_scores_codex":[0.998797,0.0000207512,0.0002249281,0.0001828206,0.0001692444,0.0006052554],"domain_scores_gemma":[0.999355,0.00006409032,0.00001973857,0.0003081254,0.00002710409,0.0002259076],"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":[0.000005183239,0.00001530758,0.1766395,0.0001015836,0.00002899227,0.00001369332,0.0002916165,0.000903854,0.8010847,0.0002724422,0.00009196023,0.02055117],"study_design_scores_gemma":[0.0003348421,0.0002859914,0.1228133,0.0005200582,0.0001103034,0.0003986431,0.00009341589,0.01184913,0.8576689,0.003718073,0.0003509487,0.001856419],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8740525,0.0004609593,0.1127371,0.000003015765,0.0006264808,0.0004034884,0.000002319795,0.002345317,0.009368825],"genre_scores_gemma":[0.5437743,0.000001468721,0.4558738,0.000004625824,0.0002516107,0.00002388423,4.897404e-7,0.00005754018,0.00001225992],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3431367,"threshold_uncertainty_score":0.9999833,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02856730050077575,"score_gpt":0.2773751062976454,"score_spread":0.2488078057968696,"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."}}