{"id":"W7116682716","doi":"10.3390/su18010132","title":"Optimizing Performance of Equipment Fleets Under Dynamic Operating Conditions: Generalizable Shift Detection and Multimodal LLM-Assisted State Labeling","year":2025,"lang":"en","type":"article","venue":"Sustainability","topic":"Machine Fault Diagnosis Techniques","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Hydro-Québec; Université du Québec à Trois-Rivières; Innovation and Economic Development Trois Rivières","funders":"","keywords":"Anomaly detection; Control chart; Statistical process control; EWMA chart; Pipeline (software); Baseline (sea); SCADA; Process (computing); False alarm; Generator (circuit theory)","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":[0.001255743,0.0009944243,0.0005983197,0.001098742,0.0002891995,0.0009344844,0.001028007,0.0005693411,0.000866352],"category_scores_gemma":[0.004718432,0.0002988233,0.0005063641,0.0004951485,0.0005099523,0.001347212,0.0009654086,0.0005963118,0.0003040452],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007479196,"about_ca_system_score_gemma":0.0007854092,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004835019,"about_ca_topic_score_gemma":0.005095811,"domain_scores_codex":[0.9992632,0.0001751994,0.00003986844,0.0002466404,0.0001870565,0.00008802484],"domain_scores_gemma":[0.9988419,0.0004696827,0.0002257854,0.0002093547,0.0002074361,0.00004584091],"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":[0.0002285269,0.0001167501,0.008403139,0.00009948292,0.00005431267,0.0001703102,0.0002190667,0.6806375,0.02590124,0.00224417,0.001316398,0.2806092],"study_design_scores_gemma":[0.000005002445,0.0000592964,0.001129184,0.000004539037,0.00000792379,0.00001893397,0.00003191351,0.9913334,0.005252649,0.001772297,0.0003747244,0.00001012846],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1290651,0.0002488475,0.863744,0.0001951289,0.00003047552,0.00007742298,0.0002011728,0.004691114,0.001746704],"genre_scores_gemma":[0.8917712,0.00005014897,0.106925,0.00006363337,0.00001650306,0.00004356299,0.0002912205,0.0001476611,0.0006911287],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004835019,"threshold_uncertainty_score":0.009613752,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00501837034820657,"score_gpt":0.2845231199149984,"score_spread":0.2795047495667918,"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."}}