{"id":"W2785460528","doi":"10.1109/epec.2017.8286162","title":"Reliability assessment of hydro dominant systems with diurnal energy management","year":2017,"lang":"en","type":"article","venue":"","topic":"Power System Reliability and Maintenance","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Reliability (semiconductor); Reliability engineering; Environmental science; Hydroelectricity; Energy storage; Inflow; Water storage; Pumped-storage hydroelectricity; Energy (signal processing); Electricity generation; Computer science; Energy management; Power (physics); Engineering; Meteorology; Statistics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004325427,0.0001487641,0.0003137265,0.00003681599,0.000102089,0.00006426713,0.0003737777,0.00004880781,0.00001607385],"category_scores_gemma":[0.000009258752,0.0001008704,0.00005721064,0.00003346909,0.00009157423,0.0001751021,0.00007774853,0.00007363655,0.00000324919],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001180564,"about_ca_system_score_gemma":0.00001566702,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004406768,"about_ca_topic_score_gemma":0.00006859771,"domain_scores_codex":[0.9989464,0.00002526976,0.0003330685,0.0002041911,0.000252335,0.0002386998],"domain_scores_gemma":[0.9986323,0.00002505522,0.0001102676,0.00109357,0.00006382172,0.00007504141],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002178228,0.0008772408,0.053407,0.01212713,0.001431064,0.0003038638,0.0003434325,0.3480967,0.007310355,0.5528179,0.0118089,0.01125865],"study_design_scores_gemma":[0.003893263,0.0005177184,0.2545455,0.00215728,0.0002034766,0.00009218137,0.0005163193,0.596081,0.009709667,0.00106256,0.1299134,0.0013077],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1188219,0.0002059671,0.4428877,0.00009453317,0.001745832,0.0005301983,0.00001482013,0.0001958904,0.4355032],"genre_scores_gemma":[0.9963929,0.00008768476,0.001707462,0.000005283762,0.00002985595,0.00005905913,0.00000108746,0.00001604977,0.001700629],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.877571,"threshold_uncertainty_score":0.4113375,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005700055311600183,"score_gpt":0.220051610117831,"score_spread":0.2143515548062308,"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."}}