{"id":"W2969888551","doi":"10.3390/en12173237","title":"A Workflow for Optimization of Flow Control Devices in SAGD","year":2019,"lang":"en","type":"article","venue":"Energies","topic":"Reservoir Engineering and Simulation Methods","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary; University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; RGL Reservoir Management","keywords":"Petroleum engineering; Steam-assisted gravity drainage; Steam injection; Completion (oil and gas wells); Workflow; Oil sands; Wellbore; Engineering; Dual (grammatical number); Enhanced oil recovery; Asphalt; Computer science; Materials science","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":[0.0001279165,0.00006293521,0.0001385963,0.00008703864,0.000005478058,0.000009135541,0.000057752,0.00004429358,0.00002825338],"category_scores_gemma":[0.00003546744,0.00006172867,0.00003248581,0.0001115756,0.00000417921,0.00007860419,0.00000382314,0.00003206445,0.000001550818],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001477224,"about_ca_system_score_gemma":0.000005119004,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004173026,"about_ca_topic_score_gemma":0.000004174167,"domain_scores_codex":[0.9996346,0.00001262357,0.0001420379,0.00006125977,0.00005408026,0.00009534789],"domain_scores_gemma":[0.9996805,0.0001694738,0.00001398466,0.000100329,0.00002220437,0.00001351371],"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":[0.00001002961,0.000003056486,0.00201053,0.00008648908,0.00001079633,9.243101e-8,0.00006857531,0.9959438,0.0005673015,0.0001268805,0.00002771845,0.001144738],"study_design_scores_gemma":[0.0006705907,0.00001208983,0.001073064,0.00003415526,0.000003102192,9.583239e-8,0.00001874161,0.9959241,0.001358326,0.00005170109,0.0007870462,0.00006700769],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4748963,0.0004072917,0.5237904,0.00001155698,0.0002117845,0.0001136006,0.000004368994,0.00008501393,0.0004797633],"genre_scores_gemma":[0.8128161,0.00002023356,0.1870012,0.000004727267,0.00002501118,0.00001867351,0.000005946406,0.00001411804,0.00009393909],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.3379199,"threshold_uncertainty_score":0.2517222,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007961912525515485,"score_gpt":0.2346182280759151,"score_spread":0.2266563155503997,"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."}}