{"id":"W2079734134","doi":"10.1002/cjce.21720","title":"An optimisation approach for increasing the profit of a commercial VGO hydrocracking process","year":2012,"lang":"en","type":"article","venue":"The Canadian Journal of Chemical Engineering","topic":"Catalysis and Hydrodesulfurization Studies","field":"Engineering","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Profit (economics); Process engineering; Volumetric flow rate; Vacuum distillation; Cracking; Net profit; Petroleum engineering; Environmental science; Waste management; Engineering; Materials science; Economics; Chemistry; Distillation; Thermodynamics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008751166,0.0007566892,0.0008397587,0.0006201007,0.0003667332,0.001083264,0.0008143185,0.0008339576,0.002345471],"category_scores_gemma":[0.0009243939,0.0005960572,0.0008367706,0.0004916832,0.0004753368,0.0006268104,0.0005852183,0.0005644667,0.000187947],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00177879,"about_ca_system_score_gemma":0.001198323,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004935722,"about_ca_topic_score_gemma":0.003994772,"domain_scores_codex":[0.9996997,0.00009630046,0.00001021087,0.00004814502,0.00008930067,0.00005635438],"domain_scores_gemma":[0.9997366,0.0001559659,0.00003492877,0.00001494403,0.00004217331,0.00001537095],"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":[0.00008249953,0.00003612513,0.0001953044,0.00004745884,0.00001724143,0.00003523036,0.00001625199,0.9835156,0.003638213,0.001700284,0.0001441233,0.01057175],"study_design_scores_gemma":[0.00001090544,0.00004489434,0.0001192306,0.000003526969,0.000008068148,0.000007834077,0.000007810921,0.9979699,0.001044146,0.0004960772,0.0002833156,0.000004146521],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3081329,0.0008121853,0.661177,0.0004651581,0.00006136894,0.0002660693,0.0001412355,0.0004325314,0.02851154],"genre_scores_gemma":[0.9637097,0.0001215258,0.03359415,0.00002700609,0.000006741761,0.00007452468,0.00004778467,0.0000402327,0.002378349],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004935722,"threshold_uncertainty_score":0.01290613,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01662410872379063,"score_gpt":0.2267358368405816,"score_spread":0.210111728116791,"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."}}