{"id":"W2013615662","doi":"10.2118/81006-ms","title":"Numerical Simulation and Screening of Oil Reservoirs for Gravity Assisted Tertiary Gas-Injection Processes","year":2003,"lang":"en","type":"article","venue":"SPE Latin American and Caribbean Petroleum Engineering Conference","topic":"Enhanced Oil Recovery Techniques","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Petroleum engineering; Residual oil; Process (computing); Displacement (psychology); Residual; Enhanced oil recovery; Micromodel; Environmental science; Fossil fuel; Water injection (oil production); Process engineering; Positive displacement meter; Water cut; Computer science; Geology; Porous medium; Waste management; Engineering; Geotechnical engineering; Mechanical engineering; Algorithm","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001365225,0.0002242275,0.000331102,0.0001405932,0.00004690587,0.00004433294,0.00007447699,0.00006524327,0.000005027384],"category_scores_gemma":[0.0002840686,0.0002445971,0.00004104394,0.0002715437,0.00008272223,0.0001445443,0.00001651921,0.000172848,1.997071e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003701622,"about_ca_system_score_gemma":0.00002651814,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006756866,"about_ca_topic_score_gemma":0.00001986869,"domain_scores_codex":[0.9990484,0.00002316459,0.0002735898,0.0002544187,0.0001383785,0.0002620781],"domain_scores_gemma":[0.9993116,0.0002429218,0.00008810626,0.0001592541,0.0001039907,0.00009407671],"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":[0.00004897273,0.00003718781,0.01229695,0.001488071,0.0001033385,0.000002423018,0.0003363373,0.8363817,0.02586992,0.000813253,0.00003135145,0.1225905],"study_design_scores_gemma":[0.0004000189,0.0002719957,0.01906516,0.0002523651,0.00004327746,0.00001080911,0.000188816,0.9567431,0.02140036,0.0001975046,0.0009518792,0.0004747265],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4158841,0.0001876664,0.5825581,0.00002083717,0.00006198343,0.00008388362,0.00002454122,0.0003556096,0.0008232805],"genre_scores_gemma":[0.962184,0.0001254514,0.03752758,0.000008943306,0.0000234613,0.00003926588,0.0000124042,0.00004255756,0.00003635896],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5462999,"threshold_uncertainty_score":0.997438,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01297167775240468,"score_gpt":0.238416246685127,"score_spread":0.2254445689327224,"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."}}