{"id":"W2048374321","doi":"10.2118/149010-pa","title":"Design of Solvent-Assisted SAGD Processes in Heterogeneous Reservoirs Using Hybrid Optimization Techniques","year":2012,"lang":"en","type":"article","venue":"Journal of Canadian Petroleum Technology","topic":"Reservoir Engineering and Simulation Methods","field":"Engineering","cited_by":35,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Saudi Aramco","keywords":"Simulated annealing; Taguchi methods; Genetic algorithm; Solvent; Computer science; Process engineering; Petroleum engineering; Mathematical optimization; Materials science; Algorithm; Mathematics; Chemistry; 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":[0.0004186867,0.0003731509,0.0005789944,0.0004453704,0.0002585755,0.0007964669,0.0004379435,0.0004886297,0.0006557623],"category_scores_gemma":[0.0003901233,0.0003134228,0.000581313,0.0003903647,0.0003971279,0.0003315488,0.0005471733,0.0003061651,0.0001006602],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006146717,"about_ca_system_score_gemma":0.0007939349,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001952234,"about_ca_topic_score_gemma":0.002052746,"domain_scores_codex":[0.9998692,0.0000290409,0.000008769774,0.00002812476,0.00003930344,0.00002539029],"domain_scores_gemma":[0.9998422,0.0000756177,0.00003241517,0.00000921134,0.00002995701,0.00001069484],"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":[0.00006545803,0.00005549896,0.0005350914,0.00009673212,0.00002003603,0.00006245155,0.00002179652,0.951062,0.0341488,0.001545629,0.00007711988,0.01230953],"study_design_scores_gemma":[0.00001060683,0.00006577044,0.0001089953,0.00000315886,0.000006478371,0.000008488414,0.000009585375,0.9925162,0.00658499,0.0003522881,0.000328924,0.000004488335],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4848591,0.0008520923,0.5077562,0.0001598316,0.00003224338,0.0001347389,0.00009403886,0.0002778399,0.005833783],"genre_scores_gemma":[0.9438037,0.0002448238,0.05474183,0.00002007332,0.00000440585,0.0001238868,0.00003810228,0.00001580425,0.001007457],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001952234,"threshold_uncertainty_score":0.004459798,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02961316228995382,"score_gpt":0.2612951453038147,"score_spread":0.2316819830138609,"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."}}