{"id":"W4412871247","doi":"10.1109/tsg.2025.3590518","title":"HMM-Based Feature Extraction and Machine Learning Methods for Event Detection and Classification in Microgrids","year":2025,"lang":"en","type":"article","venue":"IEEE Transactions on Smart Grid","topic":"Smart Grid Security and Resilience","field":"Engineering","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Feature extraction; Hidden Markov model; Artificial intelligence; Computer science; Pattern recognition (psychology); Event (particle physics); Feature (linguistics); Machine learning; Support vector machine; Speech recognition","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":[0.0008863946,0.0006279758,0.0008723759,0.001145077,0.0003132399,0.0005798645,0.0007156681,0.0005138318,0.001003667],"category_scores_gemma":[0.002097664,0.0003744554,0.0007191477,0.001148716,0.0003428115,0.0008271167,0.0004938252,0.0008537597,0.0005940956],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005064778,"about_ca_system_score_gemma":0.0005036197,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005562577,"about_ca_topic_score_gemma":0.003573691,"domain_scores_codex":[0.9995147,0.0001487955,0.00004725642,0.0001345855,0.0001108415,0.00004379116],"domain_scores_gemma":[0.9990689,0.0006010297,0.00009593374,0.00008040208,0.0001326856,0.000020952],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002444568,0.000145271,0.003961153,0.0001771497,0.0001468638,0.0001016089,0.0001179359,0.386804,0.01049053,0.002360442,0.002326173,0.5931243],"study_design_scores_gemma":[0.000004789394,0.00002493549,0.001212311,0.000008187574,0.00001199913,0.00002238391,0.00001281941,0.9941016,0.002680545,0.001462262,0.000448275,0.000009946642],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02012836,0.0005224448,0.976922,0.0001053106,0.00004852362,0.00003296273,0.0001814291,0.001591054,0.0004678553],"genre_scores_gemma":[0.6723006,0.0009013365,0.3224176,0.0001310794,0.0001118438,0.000219623,0.001115905,0.0001679195,0.002633994],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005562577,"threshold_uncertainty_score":0.01106042,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01479589597852811,"score_gpt":0.2963237233850133,"score_spread":0.2815278274064852,"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."}}