{"id":"W2015155258","doi":"10.2118/03-02-02","title":"Full Scale VAPEX Process-Climate Change Advantage and Economic Consequences A","year":2003,"lang":"en","type":"article","venue":"Journal of Canadian Petroleum Technology","topic":"Reservoir Engineering and Simulation Methods","field":"Engineering","cited_by":44,"is_retracted":false,"has_abstract":true,"ca_institutions":"Gibson Energy (Canada); Suncor Energy (Canada); Canadian Energy Research Institute","funders":"Suncor Energy Incorporated; Imperial College London; University of Saskatchewan; University of Calgary","keywords":"Oil sands; Petroleum engineering; Asphalt; Work (physics); Soil vapor extraction; Waste management; Petroleum; Environmental science; Oil field; Process (computing); Synthetic crude; Steam-assisted gravity drainage; Enhanced oil recovery; Fossil fuel; Engineering; Unconventional oil; Geology; Mechanical engineering; Materials science; Computer science; Contamination","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0006976255,0.0002836642,0.0002824972,0.0003820615,0.0005943035,0.001324608,0.0004680857,0.000636793,0.006930603],"category_scores_gemma":[0.0006543136,0.0001398682,0.0004729994,0.000672324,0.000501451,0.001070251,0.0007423583,0.000570297,0.0004613573],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002502742,"about_ca_system_score_gemma":0.0008897921,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007976305,"about_ca_topic_score_gemma":0.01074379,"domain_scores_codex":[0.9995022,0.00009050647,0.000007588579,0.00006649958,0.0002498861,0.00008333902],"domain_scores_gemma":[0.9995447,0.0001556532,0.00003989222,0.00006172749,0.0001668371,0.00003114566],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.004581085,0.001194109,0.03538467,0.0008588826,0.0001753618,0.001795087,0.0001033319,0.2248733,0.4060714,0.01674913,0.005493427,0.3027202],"study_design_scores_gemma":[0.0005556541,0.007745074,0.133819,0.0001209854,0.0002187892,0.0009839867,0.001533556,0.2658888,0.5224302,0.01488237,0.0516833,0.0001382995],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9551754,0.001104444,0.01006236,0.0005341179,0.00005506562,0.0001495674,0.0007468675,0.0001847639,0.03198739],"genre_scores_gemma":[0.9943878,0.0003158615,0.001818364,0.00002401998,0.000008652743,0.00002601651,0.0001888226,0.00001376345,0.003216578],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007976305,"threshold_uncertainty_score":0.02318513,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01118958313781365,"score_gpt":0.2436216820970635,"score_spread":0.2324320989592499,"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."}}