{"id":"W4411137150","doi":"10.1088/1361-6501/ade279","title":"Application of S-Relu activation function and adaptive dual-threshold noise reduction in fault diagnosis of RV reducer rolling bearings","year":2025,"lang":"en","type":"article","venue":"Measurement Science and Technology","topic":"Advanced Sensor and Control Systems","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"MD Precision (Canada)","funders":"","keywords":"Reducer; Reduction (mathematics); Fault (geology); Dual (grammatical number); Noise reduction; Noise (video); Computer science; Control theory (sociology); Automotive engineering; Materials science; Acoustics; Physics; Engineering; Mathematics; Geology; Artificial intelligence; Geometry; Thermodynamics","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":[0.0006364984,0.0007532702,0.0006578329,0.0006743736,0.0002542327,0.0004397509,0.0008806109,0.0009398476,0.0008854041],"category_scores_gemma":[0.001422239,0.0002450415,0.0005113649,0.0002914417,0.0004235537,0.0006254405,0.0004141428,0.0004760741,0.0002059037],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004213334,"about_ca_system_score_gemma":0.0004681183,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003820808,"about_ca_topic_score_gemma":0.002600828,"domain_scores_codex":[0.9995803,0.00008251661,0.00002403535,0.0001044927,0.0001572811,0.00005136494],"domain_scores_gemma":[0.9995968,0.0001191452,0.00004938113,0.00003191272,0.0001806187,0.00002214362],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0007840436,0.0002877575,0.004925684,0.0003012327,0.000114791,0.0005341947,0.0002441009,0.4409308,0.128572,0.002842488,0.001913904,0.4185489],"study_design_scores_gemma":[0.000005464373,0.00006891636,0.0004814518,0.00000498753,0.000008804434,0.00004192589,0.00001281964,0.9894153,0.009602489,0.0001883471,0.0001614989,0.00000799374],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1858062,0.0009982355,0.8091564,0.00035015,0.0001225513,0.00006191107,0.0000364659,0.001382481,0.002085513],"genre_scores_gemma":[0.9525606,0.0001369882,0.045901,0.00006385352,0.00001844922,0.00003265975,0.00002911341,0.00002234119,0.001235],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003820808,"threshold_uncertainty_score":0.007597148,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01273905949324034,"score_gpt":0.217594069940571,"score_spread":0.2048550104473306,"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."}}