{"id":"W1967209296","doi":"10.1109/pes.2010.5588070","title":"A mixed integer nonlinear program for electric generation expansion with energy and capacity pricing","year":2010,"lang":"en","type":"article","venue":"","topic":"Electric Power System Optimization","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Profit (economics); Electricity; Mathematical optimization; Incentive; Integer (computer science); Commodity; Linear programming; Computer science; Incentive compatibility; Nonlinear programming; Integer programming; Nonlinear system; Microeconomics; Economics; Operations research; Mathematics; Engineering; Electrical engineering; Finance","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":[0.001795639,0.001022754,0.0007913841,0.0004634711,0.0004024357,0.001236435,0.001246469,0.001392189,0.007278334],"category_scores_gemma":[0.002524768,0.0005563325,0.0006524097,0.0006461932,0.0009730902,0.001338478,0.00112537,0.001441325,0.0006295122],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001605121,"about_ca_system_score_gemma":0.001943874,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003377928,"about_ca_topic_score_gemma":0.004049091,"domain_scores_codex":[0.9993445,0.0003202715,0.00001737014,0.0001022771,0.0001540815,0.00006146714],"domain_scores_gemma":[0.9993088,0.0004860778,0.00005691283,0.00002428894,0.00008942961,0.00003437552],"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":[0.00003681032,0.00006509406,0.0001385548,0.0000801826,0.00001405566,0.00006888114,0.00005050234,0.8775637,0.0006077737,0.1083141,0.001423461,0.01163687],"study_design_scores_gemma":[0.00001487608,0.00002302095,0.00003442787,0.000007238228,0.000003968507,0.00001085396,0.00000872188,0.9837642,0.0001411447,0.01434269,0.001643974,0.000004813135],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.008706417,0.0001487856,0.9743401,0.0004692392,0.00004501117,0.0001163015,0.0001717849,0.00008989,0.01591242],"genre_scores_gemma":[0.4322344,0.0005242519,0.5331717,0.0002897648,0.0001134455,0.001227503,0.0003637629,0.0001493675,0.03192587],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007278334,"threshold_uncertainty_score":0.02434844,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009751282308505103,"score_gpt":0.194923256669384,"score_spread":0.1851719743608788,"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."}}