{"id":"W2091667015","doi":"10.1016/j.enpol.2009.05.050","title":"Development of an inexact optimization model for coupled coal and power management in North China","year":2009,"lang":"en","type":"article","venue":"Energy Policy","topic":"Water resources management and optimization","field":"Engineering","cited_by":54,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Regina","funders":"Major State Basic Research Development Program of China; Ministry of Science and Technology","keywords":"Coal; Constraint (computer-aided design); Context (archaeology); Mathematical optimization; Linear programming; Integer programming; Interval (graph theory); Reliability (semiconductor); Operations research; Computer science; Electric power system; Goal programming; Programming paradigm; Reliability engineering; Power (physics); Engineering; Mathematics; Waste management","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":[0.0008090386,0.000815366,0.001296508,0.0004651374,0.001024041,0.001545124,0.001245252,0.00182769,0.002382032],"category_scores_gemma":[0.001470518,0.0008047516,0.0006849281,0.0004898987,0.0009293606,0.0009412845,0.001337584,0.0009695922,0.0002162371],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001735583,"about_ca_system_score_gemma":0.004529466,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1179656,"about_ca_topic_score_gemma":0.05620382,"domain_scores_codex":[0.9997132,0.00009571925,0.00001624487,0.00006313933,0.00006110389,0.00005050534],"domain_scores_gemma":[0.9995692,0.0001963872,0.00005073856,0.00002898088,0.0001078749,0.00004678349],"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":[0.000007568258,0.000006484634,0.000197641,0.000006945958,0.000004105223,0.00001818205,0.000008548817,0.9982623,0.00007309651,0.0006632395,0.00006514545,0.0006867528],"study_design_scores_gemma":[0.000003576136,0.000003994608,0.00005431768,6.941733e-7,0.000001792197,9.769631e-7,0.000004088078,0.9996594,0.00003149511,0.0001797217,0.00005830905,0.000001545048],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.519046,0.0006199696,0.4445865,0.001341259,0.0001968725,0.0001951682,0.0006147558,0.0006337857,0.03276566],"genre_scores_gemma":[0.9807905,0.0001638125,0.01378304,0.00006569065,0.00002080871,0.0001344186,0.0001709925,0.00006522365,0.004805658],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1179656,"threshold_uncertainty_score":0.2345579,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007534514572370539,"score_gpt":0.2086650485396884,"score_spread":0.2011305339673179,"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."}}