{"id":"W1979018543","doi":"10.2118/173485-stu","title":"Modeling Displacement Efficiency Improvement During Solvent Aided-SAGD","year":2014,"lang":"en","type":"article","venue":"SPE Annual Technical Conference and Exhibition","topic":"Enhanced Oil Recovery Techniques","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; Alberta Innovates - Technology Futures; CMG Reservoir Simulation Foundation","keywords":"Displacement (psychology); Solvent; Materials science; Mechanics; Residual oil; Petroleum engineering; Core (optical fiber); Chemistry; Physics; Composite material; Geology; Organic chemistry","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"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":[0.0003107761,0.0001988994,0.0002956846,0.0002540302,0.0001362044,0.0003595402,0.0003588948,0.0004173148,0.0007684896],"category_scores_gemma":[0.0004452216,0.000137143,0.0003440495,0.0002053538,0.0003143918,0.000343907,0.0002722766,0.0002065024,0.0001653034],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006531461,"about_ca_system_score_gemma":0.0003999027,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003835206,"about_ca_topic_score_gemma":0.003394081,"domain_scores_codex":[0.9998802,0.00001690126,0.000007268418,0.0000253715,0.00004926871,0.00002100697],"domain_scores_gemma":[0.9998418,0.00008892266,0.00002466278,0.00001379562,0.00002634293,0.000004391447],"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":[0.0001032665,0.00005920818,0.002709052,0.000138993,0.00001140318,0.0001209929,0.00005596477,0.8530405,0.1290225,0.00140361,0.00008695423,0.01324766],"study_design_scores_gemma":[0.000002567442,0.00003955146,0.0005924544,0.000002415655,0.000003567812,0.00001608715,0.000008471981,0.9585007,0.04045483,0.00007765543,0.0002970694,0.000004557712],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7989743,0.0003449329,0.1967495,0.00007756221,0.0000153392,0.00006636981,0.0002170549,0.0003455621,0.003209505],"genre_scores_gemma":[0.9917859,0.0001310076,0.006883705,0.000005913444,8.780443e-7,0.00002542714,0.00004979061,0.00001194272,0.001105455],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003835206,"threshold_uncertainty_score":0.007625759,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009059918652466858,"score_gpt":0.2306180903023743,"score_spread":0.2215581716499074,"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."}}