{"id":"W2743349201","doi":"10.3390/en10081176","title":"Risk Assessment of Micro Energy Grid Protection Layers","year":2017,"lang":"en","type":"article","venue":"Energies","topic":"Microgrid Control and Optimization","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Tech University","funders":"Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada","keywords":"Reliability engineering; Fault tree analysis; Hazard analysis; Grid; Electricity; Hazard; Energy (signal processing); Computer science; Risk assessment; Risk analysis (engineering); Environmental science; Engineering; Mathematics; Medicine","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":[0.001034493,0.000942523,0.0003719568,0.0009477685,0.0002893647,0.001000044,0.00075855,0.0005020631,0.001710877],"category_scores_gemma":[0.002245249,0.000292514,0.0007547123,0.0003736088,0.0004293138,0.001358418,0.001011637,0.0004970066,0.0001470119],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008630464,"about_ca_system_score_gemma":0.0007713256,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002306895,"about_ca_topic_score_gemma":0.001455406,"domain_scores_codex":[0.9992936,0.0002174034,0.00002618209,0.00009359315,0.0002888913,0.00008034558],"domain_scores_gemma":[0.9988927,0.00050449,0.0002550192,0.0001002236,0.0002068936,0.00004069849],"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":[0.00005299038,0.00001892846,0.003555186,0.00004354034,0.00004269681,0.0001117177,0.00006343624,0.9595997,0.003055575,0.01367822,0.000369855,0.01940812],"study_design_scores_gemma":[0.000003746245,0.00004838965,0.001016392,0.00001234241,0.00002100553,0.00006586881,0.00004946844,0.987487,0.001819159,0.008764941,0.0007030246,0.000008764192],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1948394,0.0004931409,0.7922966,0.0003115289,0.00002609106,0.0001157485,0.0002608669,0.000268438,0.01138823],"genre_scores_gemma":[0.9758072,0.0001707261,0.02225018,0.00001573936,0.000009924664,0.00003754859,0.00008529097,0.00001726502,0.0016061],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002306895,"threshold_uncertainty_score":0.006261885,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005783999027681707,"score_gpt":0.2073962464466506,"score_spread":0.2016122474189689,"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."}}