{"id":"W1992879923","doi":"10.2118/2008-033","title":"Post-Cold Production Solvent Vapor Extraction (SVX) Process Performance Evaluation by Numerical Simulation","year":2008,"lang":"en","type":"article","venue":"Canadian International Petroleum Conference","topic":"Process Optimization and Integration","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"Saskatchewan Research Council (Canada)","funders":"","keywords":"Extraction (chemistry); Process (computing); Process simulation; Solvent extraction; Process engineering; Production (economics); Computer simulation; Solvent; Materials science; Computer science; Environmental science; Chemistry; Simulation; Engineering; Chromatography; Organic chemistry","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0006644679,0.0005352558,0.0008032056,0.0005431838,0.0006596319,0.0008309947,0.0006335235,0.001035242,0.0017929],"category_scores_gemma":[0.001388965,0.0002732409,0.0008310138,0.0004849069,0.0005740539,0.0004972028,0.0003997385,0.0005547276,0.0002372264],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001169583,"about_ca_system_score_gemma":0.0009277177,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01275766,"about_ca_topic_score_gemma":0.004640694,"domain_scores_codex":[0.9997041,0.00005054535,0.00001537365,0.00004162341,0.0001193662,0.00006900894],"domain_scores_gemma":[0.9985556,0.0008137378,0.0001750785,0.00008515388,0.0003327499,0.00003767924],"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":[0.00009574104,0.00007133969,0.001207309,0.00006402897,0.000009965956,0.00005106485,0.0000313412,0.9886276,0.006026444,0.0004883268,0.0001119179,0.003214865],"study_design_scores_gemma":[0.0000101466,0.00007279344,0.0002432539,0.000003289534,0.000003577736,0.000005637701,0.00001305433,0.9947389,0.004698062,0.00007700862,0.0001283733,0.000005959065],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9372431,0.000377915,0.05084729,0.0001814662,0.00004109102,0.0001385356,0.0003735138,0.0004473976,0.01034962],"genre_scores_gemma":[0.9909769,0.00009528131,0.00771991,0.00001173577,0.000003056848,0.00006596231,0.0001063212,0.00001512794,0.001005668],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01275766,"threshold_uncertainty_score":0.02536678,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0209879369799675,"score_gpt":0.2598766095835034,"score_spread":0.2388886726035359,"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."}}