{"id":"W4403839850","doi":"10.18280/jesa.570501","title":"Advanced Diagnosis of Air Gap Eccentricity in Three-Phase Induction Motor Using DWT Decomposition and AI Techniques","year":2024,"lang":"en","type":"article","venue":"Journal Européen des Systèmes Automatisés","topic":"Magnetic Properties and Applications","field":"Materials Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Induction motor; Decomposition; Phase (matter); Computer science; Eccentricity (behavior); Artificial intelligence; Engineering; Psychology; Physics; Electrical engineering; Biology","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":[0.0004346666,0.0001369712,0.0002319742,0.0001760639,0.0001683581,0.0001821252,0.0001382144,0.00005853689,0.0001290069],"category_scores_gemma":[0.00006769335,0.0001110385,0.00005244758,0.0003090462,0.0001119677,0.0005259128,0.00007053022,0.0001711396,0.000005629366],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001628603,"about_ca_system_score_gemma":0.00005758306,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000115423,"about_ca_topic_score_gemma":0.00001826888,"domain_scores_codex":[0.9986803,0.0001194073,0.000535792,0.0002125216,0.0002473556,0.0002046425],"domain_scores_gemma":[0.9994364,0.00006681015,0.0001839464,0.0001364986,0.00009458396,0.00008177084],"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":[0.00002777832,0.0001214867,0.0009038366,0.0002619883,0.000007727616,0.00002468096,0.0002001175,0.0002070635,0.5747148,0.0004170017,0.00007184754,0.4230417],"study_design_scores_gemma":[0.001111695,0.001145695,0.1207661,0.004232124,0.0001548571,0.001712079,0.0002206226,0.2094956,0.6401088,0.01912588,0.001322613,0.0006039115],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9737763,0.002782012,0.02236249,0.0003111024,0.0001897728,0.0003322719,0.00002345238,0.0001262393,0.00009640511],"genre_scores_gemma":[0.9790813,0.0005194581,0.02017935,0.0000443818,0.00009269534,0.00004303943,8.497293e-7,0.00001999281,0.00001889437],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4224378,"threshold_uncertainty_score":0.452802,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02767572739783102,"score_gpt":0.3164187790189454,"score_spread":0.2887430516211144,"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."}}