{"id":"W4409651746","doi":"10.1049/enc2.70006","title":"Multi‐phase microgrid resiliency assessment framework against extreme weather events","year":2025,"lang":"en","type":"article","venue":"Energy Conversion and Economics","topic":"Smart Grid Security and Resilience","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada","keywords":"Microgrid; Extreme weather; Phase (matter); Environmental science; Computer science; Climate change; Geology; Artificial intelligence; Chemistry; Oceanography; Control (management)","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001799998,0.0007288665,0.0006871,0.0008642071,0.0004662237,0.001029292,0.001018801,0.0007303523,0.001736571],"category_scores_gemma":[0.002005135,0.0003955582,0.0006183137,0.0005443565,0.0007366668,0.0007770482,0.0009930094,0.0005325388,0.0001643698],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001161807,"about_ca_system_score_gemma":0.00128223,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01144923,"about_ca_topic_score_gemma":0.008833333,"domain_scores_codex":[0.999513,0.0002675179,0.0000155175,0.00005515298,0.0001016534,0.00004716036],"domain_scores_gemma":[0.9994909,0.0002382748,0.00008644428,0.00002797291,0.0001119565,0.00004435069],"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":[0.000008062157,0.000005514717,0.0001697583,0.000005882665,0.000007670737,0.00002068805,0.000006572051,0.995212,0.0001114616,0.003239051,0.00004858775,0.001164766],"study_design_scores_gemma":[0.000001690606,0.000007923668,0.00004444048,0.000002234909,0.000002464682,0.000003701363,0.000003513194,0.9987979,0.00002745518,0.001033241,0.00007365002,0.000001741216],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06192103,0.0003081849,0.9299208,0.0002743669,0.00002717318,0.0001255636,0.0001318526,0.0003306291,0.006960454],"genre_scores_gemma":[0.9566011,0.0001728753,0.04124475,0.00002581447,0.00001798192,0.0001017874,0.00007091953,0.0000235818,0.001741068],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01144923,"threshold_uncertainty_score":0.02276516,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009585628245418766,"score_gpt":0.2339958051373099,"score_spread":0.2244101768918912,"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."}}