{"id":"W2922013388","doi":"10.1007/s11081-019-09426-5","title":"Multistage stochastic capacity planning of partially upgraded bitumen production with hybrid solution method","year":2019,"lang":"en","type":"article","venue":"Optimization and Engineering","topic":"Energy, Environment, and Transportation Policies","field":"Energy","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"Natural Resources Canada","keywords":"Variable (mathematics); Mathematical optimization; Asphalt; Computer science; Set (abstract data type); Production (economics); Production planning; Random variable; Stochastic modelling; Mathematics; Statistics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.002045092,0.001302871,0.002964013,0.00137801,0.0007496693,0.001832208,0.001775519,0.001762722,0.004285444],"category_scores_gemma":[0.002219719,0.001884819,0.001799735,0.001876176,0.00106786,0.001150349,0.001296672,0.00126381,0.0002583237],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0019447,"about_ca_system_score_gemma":0.002530019,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02412912,"about_ca_topic_score_gemma":0.0163457,"domain_scores_codex":[0.998946,0.0004125443,0.0000403322,0.0001316078,0.0002136658,0.0002558077],"domain_scores_gemma":[0.9983248,0.001100733,0.0001477311,0.00005065665,0.0002575608,0.0001185151],"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":[0.0000160577,0.000005452638,0.00004741287,0.00001205945,0.000008179261,0.00001461773,0.000003778377,0.9984806,0.00009601138,0.0005659426,0.00004213647,0.0007077674],"study_design_scores_gemma":[0.000003755017,0.000009285314,0.00003319812,0.000001921236,0.00000320801,0.000001393867,0.000002584909,0.9994954,0.00005308446,0.0003557842,0.00003784856,0.000002472989],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1165123,0.0007568236,0.8707795,0.0003664223,0.0001334293,0.0002252682,0.0004052956,0.0003203798,0.01050059],"genre_scores_gemma":[0.9501659,0.0002833942,0.04355371,0.00006516203,0.00003646874,0.0003473782,0.000250942,0.00005751225,0.005239442],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02412912,"threshold_uncertainty_score":0.04797733,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01025784337057726,"score_gpt":0.2062673190846438,"score_spread":0.1960094757140666,"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."}}