{"id":"W2154935705","doi":"10.1109/icsssm.2010.5530272","title":"Managing financial risks for natural gas-fired power plants","year":2010,"lang":"en","type":"article","venue":"","topic":"Electric Power System Optimization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Deregulation; Electricity; Valuation (finance); Natural gas; Electricity generation; Business; Environmental economics; Risk management; Electricity price; Natural gas prices; Electric power industry; Natural resource economics; Finance; Industrial organization; Power (physics); Economics; Engineering; Waste management; Electrical engineering; Market economy","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":[0.003072623,0.0009317225,0.0006184051,0.000916264,0.0006185398,0.002234573,0.0006660196,0.000973764,0.0009757385],"category_scores_gemma":[0.007631917,0.0003334205,0.00037988,0.0005837326,0.0006893865,0.002847646,0.001294746,0.0008715833,0.0000719186],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001377179,"about_ca_system_score_gemma":0.001069701,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001889776,"about_ca_topic_score_gemma":0.00215234,"domain_scores_codex":[0.9990129,0.0005135973,0.00003913571,0.00007360177,0.0002324877,0.0001281586],"domain_scores_gemma":[0.9971855,0.001758308,0.0005763112,0.00007011373,0.000241195,0.0001685279],"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":[0.0007873388,0.0001724226,0.01322202,0.0001282754,0.0001200939,0.0008830079,0.0003140838,0.8671915,0.003668825,0.03569064,0.001433261,0.07638849],"study_design_scores_gemma":[0.00003891608,0.0001975528,0.003837171,0.00003458427,0.00003725366,0.000189838,0.0004072064,0.9392664,0.001928878,0.05278151,0.001241574,0.00003906537],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7818789,0.002208469,0.2021979,0.002556052,0.00005682314,0.0001805376,0.0001534832,0.000105855,0.01066195],"genre_scores_gemma":[0.9928884,0.0003898389,0.006182416,0.00001726537,0.00002207172,0.00001844127,0.00002503457,0.000004246874,0.0004523263],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003072623,"threshold_uncertainty_score":0.01624978,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007355709453784305,"score_gpt":0.2177103739311182,"score_spread":0.2103546644773339,"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."}}