{"id":"W2776697730","doi":"10.5419/bjpg2017-0018","title":"COMBINING MIXED-COMPOSITION PETROLEUM STREAMS USING PROXY MODELS OF EQUATION OF STATE FOR COMPOSITIONAL INTEGRATED PRODUCTION MANAGEMENT","year":2017,"lang":"en","type":"article","venue":"Brazilian Journal of Petroleum and Gas","topic":"Reservoir Engineering and Simulation Methods","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Universidade Estadual de Campinas; Petrobras; Energi Simulation; U.S. Department of Energy","keywords":"Computer science; Compositional data; Proxy (statistics); Composition (language); Data mining; Reservoir simulation; Petroleum; Petroleum engineering; Engineering; Geology; Machine learning","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000589714,0.0001309637,0.0003000925,0.0002408204,0.0001135024,0.00004897441,0.0001321665,0.00004424591,0.000002290166],"category_scores_gemma":[0.00002616543,0.0001251316,0.00009692233,0.00004374135,0.00005231487,0.0004679767,0.00001703302,0.0001214052,9.160006e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004947139,"about_ca_system_score_gemma":0.00001764947,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005387901,"about_ca_topic_score_gemma":8.714858e-7,"domain_scores_codex":[0.9989357,0.00004405152,0.0005528485,0.0001019449,0.0002309433,0.0001344869],"domain_scores_gemma":[0.9990658,0.00004657804,0.0004292548,0.000165004,0.0002314066,0.0000619957],"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":[0.0001568224,0.00004362942,0.0007265746,0.0003386403,0.0001264191,0.000001938765,0.000117145,0.9573439,0.03564953,0.0003506114,0.00002044064,0.005124339],"study_design_scores_gemma":[0.001264007,0.0001756918,0.002312199,0.000440976,0.0000741621,0.00002415249,0.0000956095,0.9651783,0.02781915,0.002477166,0.00003351027,0.0001050617],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6135964,0.0001033171,0.3858196,0.00004328077,0.0002553032,0.00007675151,0.00001480815,0.00001013077,0.00008041813],"genre_scores_gemma":[0.9367214,0.00007739387,0.06306509,0.000001211807,0.00006846271,0.000003264316,0.00001463586,0.00001930236,0.00002916695],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3231251,"threshold_uncertainty_score":0.5102717,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0273336006385669,"score_gpt":0.2772978329848013,"score_spread":0.2499642323462344,"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."}}