{"id":"W2587367577","doi":"10.2118/182708-ms","title":"Numerical Modelling of Hybrid Steam and In-Situ Combustion Performance for Oil Sands","year":2017,"lang":"en","type":"article","venue":"SPE Reservoir Simulation Conference","topic":"Petroleum Processing and Analysis","field":"Chemistry","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Nexen (Canada); University of Calgary","funders":"Alberta Innovates - Technology Futures","keywords":"Steam injection; Enhanced oil recovery; Secondary air injection; Petroleum engineering; Combustion; Oil sands; Residual oil; Water injection (oil production); Superheated steam; Boiler (water heating); Environmental science; Waste management; Nuclear engineering; Materials science; Engineering; Chemistry; 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":[0.0001608259,0.00009755482,0.000213082,0.00005398359,0.0001955273,0.00008328956,0.0001895641,0.00004897383,0.00002776309],"category_scores_gemma":[0.000119332,0.00009594209,0.00003967229,0.00003595856,0.00006484306,0.0002703906,0.00003827301,0.0001037621,0.000001130637],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002297783,"about_ca_system_score_gemma":0.00005257778,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004033415,"about_ca_topic_score_gemma":0.00001117044,"domain_scores_codex":[0.9992418,0.000008615622,0.0002402655,0.0002106315,0.0001539581,0.0001447607],"domain_scores_gemma":[0.9991728,0.0000926139,0.0002269726,0.0002892461,0.0001737568,0.00004462179],"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":[0.0001327417,0.00003407731,0.01488308,0.0004371018,0.00001285212,6.428016e-7,0.00005946014,0.9392372,0.00480731,0.00002286258,0.000001538527,0.04037116],"study_design_scores_gemma":[0.0006171445,0.0000141025,0.000634454,0.0002453752,0.000017969,5.640894e-7,0.00002692434,0.9704431,0.02754214,0.000196921,0.0001559748,0.0001053368],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9562113,0.00009441425,0.03515362,0.00009350877,0.00001523366,0.000007234054,0.000007157869,0.00001594542,0.008401568],"genre_scores_gemma":[0.9979171,0.0001806242,0.0006077134,0.000003660156,0.00004164235,0.000005946073,0.00002156242,0.000008130783,0.001213581],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04170582,"threshold_uncertainty_score":0.3912405,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06604251702652911,"score_gpt":0.3076431117870692,"score_spread":0.2416005947605401,"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."}}