{"id":"W4417339022","doi":"10.1109/ictai66417.2025.00015","title":"FiLSTM: Fuzzy Rule Induction for LSTM Model: The Case of Predictive Maintenance","year":2025,"lang":"","type":"article","venue":"","topic":"Machine Fault Diagnosis Techniques","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Rimouski","funders":"","keywords":"Interpretability; Robustness (evolution); Fuzzy logic; Predictive maintenance; Neuro-fuzzy; Adaptive neuro fuzzy inference system; Fuzzy rule; Fuzzy control system","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":[0.0005936321,0.0006362761,0.0004090253,0.0003089304,0.0002468612,0.0006104602,0.0009217304,0.001317592,0.001748698],"category_scores_gemma":[0.002067406,0.0002203728,0.0003313813,0.0003395406,0.0004154773,0.001130095,0.0004866947,0.00114623,0.0005019966],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005615165,"about_ca_system_score_gemma":0.0005459764,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005377358,"about_ca_topic_score_gemma":0.005782025,"domain_scores_codex":[0.9998065,0.00003616558,0.00001406297,0.0000724125,0.00004304319,0.0000279006],"domain_scores_gemma":[0.9995671,0.0002312647,0.00003512707,0.00005918737,0.00008898669,0.00001832842],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003353272,0.00008490739,0.002287864,0.0002922135,0.000098558,0.0007640354,0.0001707297,0.5927674,0.01860659,0.01813707,0.008039623,0.3584157],"study_design_scores_gemma":[0.000003399152,0.00001545746,0.0001309675,0.000007948292,0.000006737746,0.00005003528,0.000006693938,0.9911478,0.0027748,0.005106883,0.0007455794,0.000003676429],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0686512,0.001633671,0.9205526,0.001240186,0.0002302188,0.00005202267,0.0004011248,0.003210151,0.004028929],"genre_scores_gemma":[0.8378905,0.0004579997,0.1581963,0.0002241734,0.00007142742,0.00005104829,0.000299539,0.000104983,0.002703932],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.005377358,"threshold_uncertainty_score":0.01069212,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01104829293681845,"score_gpt":0.2964525910428285,"score_spread":0.28540429810601,"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."}}