{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00004108119,0.00009275998,0.00009363349,0.0003103487,0.00002393701,0.00001646919,0.00006385073,0.0000261336,0.000002551453],"category_scores_gemma":[0.000001540986,0.00009548864,0.00001162887,0.000182079,0.00000554541,0.000117748,0.00001614742,0.00001777463,1.188456e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003867716,"about_ca_system_score_gemma":0.000005572034,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001501596,"about_ca_topic_score_gemma":0.00009008189,"domain_scores_codex":[0.9995248,0.000003885483,0.0001725685,0.00009790539,0.00006617283,0.0001346747],"domain_scores_gemma":[0.9998505,0.000001750691,0.00002454826,0.00008311735,0.00000787385,0.00003226881],"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":[0.00001438291,0.00002755686,0.00003245762,0.00001790955,0.00001345048,4.019854e-7,0.000873467,0.991681,0.00001204469,0.0030462,0.00001386442,0.004267272],"study_design_scores_gemma":[0.0005105037,0.00002075032,0.003502949,0.000006393926,0.000005090569,1.240073e-7,0.00001508672,0.9952084,0.00007071788,0.0001018003,0.0004563775,0.0001017775],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2566253,0.00001741169,0.7405297,0.00003153442,0.00001311374,0.0001229263,0.000001625995,0.00005714379,0.002601322],"genre_scores_gemma":[0.9196715,0.00004022209,0.07986245,0.00004613718,0.00001807577,0.00001588168,0.00008868195,0.00001392573,0.0002430964],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6630462,"threshold_uncertainty_score":0.3893914,"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."}}