{"id":"W2906588870","doi":"10.1109/pesgm.2018.8586552","title":"Modeling Hourly Original Operating Reserve Prices in Electricity Market","year":2018,"lang":"en","type":"article","venue":"","topic":"Electric Power System Optimization","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary; Independent Electricity System Operator","funders":"","keywords":"Econometrics; Electricity market; Electricity; Market price; Markov process; Economics; Markov chain; Computer science; Microeconomics; Statistics; Mathematics; Engineering; Electrical engineering","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":[0.001098432,0.0004216975,0.0005120289,0.0002702381,0.0001373778,0.0008313103,0.0008436562,0.0007110165,0.0007164747],"category_scores_gemma":[0.003770895,0.0003572912,0.0005141611,0.0003377915,0.0003840713,0.001257815,0.0002686905,0.0007906763,0.0001196832],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005817314,"about_ca_system_score_gemma":0.0004742689,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005928804,"about_ca_topic_score_gemma":0.003856512,"domain_scores_codex":[0.999741,0.0001182281,0.0000136215,0.00004535736,0.00004999336,0.00003183464],"domain_scores_gemma":[0.9983346,0.001286534,0.0001948868,0.00007070729,0.00008117291,0.0000320505],"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":[0.00002451763,0.00001980753,0.0005620801,0.000008959667,0.000006480512,0.0000231332,0.00001230889,0.9922488,0.0002378699,0.004884548,0.00009792932,0.001873507],"study_design_scores_gemma":[0.000001115517,0.000003510839,0.0000965724,3.930299e-7,7.539774e-7,0.000002595898,0.000001004167,0.9992544,0.0000369971,0.0005862798,0.00001520501,0.000001130117],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5866032,0.0002640516,0.4086249,0.0002671509,0.0000465925,0.00004707334,0.0003768918,0.0002580758,0.003512116],"genre_scores_gemma":[0.9915451,0.0001138031,0.007114896,0.00001770153,0.00001436179,0.00002462963,0.0001274909,0.00001623027,0.001025783],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005928804,"threshold_uncertainty_score":0.01178861,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01071672375991108,"score_gpt":0.2289165980280518,"score_spread":0.2181998742681407,"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."}}