{"id":"W1981336992","doi":"10.1016/j.petrol.2013.08.015","title":"Numerical simulation of heavy-oil/bitumen recovery by solvent injection at elevated temperatures","year":2013,"lang":"en","type":"article","venue":"Journal of Petroleum Science and Engineering","topic":"Enhanced Oil Recovery Techniques","field":"Engineering","cited_by":15,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Asphalt; Petroleum engineering; Solvent; Environmental science; Enhanced oil recovery; Chemistry; Waste management; Materials science; Geology; Organic chemistry; Engineering; Composite material","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003684525,0.000120681,0.0002056487,0.0002988529,0.00004954057,0.00006156085,0.0001346672,0.00005293698,0.00001701308],"category_scores_gemma":[0.0001234234,0.0001078307,0.00004922607,0.0003460355,0.00004126527,0.0009320315,0.00002349507,0.0001985473,0.000002006868],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002712286,"about_ca_system_score_gemma":0.0000278279,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001027442,"about_ca_topic_score_gemma":3.688586e-7,"domain_scores_codex":[0.9989332,0.000006871575,0.000361776,0.0001016097,0.0003805189,0.0002160496],"domain_scores_gemma":[0.9994548,0.00006018087,0.0001030565,0.00008882218,0.0001857498,0.0001073899],"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":[0.000005432498,0.000006044638,0.0001069402,0.00002777034,0.00000777385,5.94115e-7,0.00002482105,0.4844275,0.5138693,0.000002147217,0.0003621254,0.001159623],"study_design_scores_gemma":[0.0001612524,0.0002492498,0.001615302,0.0001270397,0.000008479306,0.00004944192,0.00002064541,0.6073892,0.3895196,0.00003263016,0.0006790956,0.0001481283],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9788863,0.0004493817,0.02006226,0.00002928291,0.0003145052,0.00002827682,0.000001560795,0.0000718639,0.0001565628],"genre_scores_gemma":[0.9978877,0.0002389123,0.001745433,0.00001195263,0.00005231519,0.000003521878,6.063657e-7,0.00001554997,0.0000439929],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1243497,"threshold_uncertainty_score":0.4397208,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004210797134432709,"score_gpt":0.2071630023021698,"score_spread":0.2029522051677371,"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."}}