{"id":"W1976302408","doi":"10.2118/117327-ms","title":"Increasing Oil Recovery from Heavy Oil Waterfloods","year":2008,"lang":"en","type":"article","venue":"International Thermal Operations and Heavy Oil Symposium","topic":"Reservoir Engineering and Simulation Methods","field":"Engineering","cited_by":39,"is_retracted":false,"has_abstract":true,"ca_institutions":"Saskatchewan Research Council (Canada)","funders":"","keywords":"Petroleum engineering; Fraction (chemistry); Oil viscosity; Sweet spot; Light crude oil; Permeability (electromagnetism); Window (computing); Volume fraction; Environmental science; Viscosity; Geology; Computer science; Chemistry; Materials science; Chromatography; Simulation","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":[0.0008445687,0.0003292349,0.0004197874,0.001665621,0.000543594,0.0008803881,0.0005872558,0.0002332099,0.001444845],"category_scores_gemma":[0.004540656,0.0001381617,0.0005281669,0.002082211,0.0007731491,0.000433983,0.0007171258,0.0003167396,0.0002953821],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001968553,"about_ca_system_score_gemma":0.001812688,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.4205571,"about_ca_topic_score_gemma":0.6397142,"domain_scores_codex":[0.9989428,0.00005119099,0.00005171485,0.0002830717,0.0005054066,0.0001659405],"domain_scores_gemma":[0.9970742,0.0005348774,0.0008186817,0.0002402714,0.001166548,0.0001654223],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005344389,0.00003226859,0.9027626,0.0004094463,0.0002539017,0.0001954411,0.001097828,0.002293595,0.02371129,0.0001930732,0.001182087,0.06733406],"study_design_scores_gemma":[0.000001872872,0.00008068815,0.9908812,0.00002025205,0.00004322477,0.00004735565,0.000750189,0.001201015,0.0045144,0.00004014283,0.002401126,0.00001860298],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9934179,0.0003019082,0.001532886,0.00003264887,0.000004537191,0.0000343816,0.003371399,0.0001257509,0.001178626],"genre_scores_gemma":[0.9927665,0.0002067225,0.002072473,0.00002102507,0.000002428883,0.00001805925,0.003294123,0.00003277101,0.001585796],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4205571,"threshold_uncertainty_score":0.8362184,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01760346679236629,"score_gpt":0.2528927414205471,"score_spread":0.2352892746281808,"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."}}