{"id":"W4236887914","doi":"10.2118/2009-115","title":"Advanced Solvent-Additive Processes via Genetic Optimization","year":2009,"lang":"en","type":"article","venue":"Canadian International Petroleum Conference","topic":"Reservoir Engineering and Simulation Methods","field":"Engineering","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"Laricina Energy (Canada)","funders":"","keywords":"Citation; Computer science; Download; Solvent; Operations research; Information retrieval; Library science; Engineering; World Wide Web; Chemistry; Organic chemistry","routes":{"ca_aff":true,"ca_fund":false,"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":[0.00004496329,0.000138552,0.0001077283,0.0002348704,0.00004804862,0.00008952223,0.0002434715,0.00006313858,0.000466053],"category_scores_gemma":[0.0000999492,0.0001615001,0.00002926359,0.0001415825,0.00001533714,0.0002065095,0.000005033306,0.0001215121,0.00002994224],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002130236,"about_ca_system_score_gemma":0.0001606203,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000317754,"about_ca_topic_score_gemma":0.001844076,"domain_scores_codex":[0.9992526,0.00001187762,0.0001790298,0.000162008,0.0001627062,0.0002317596],"domain_scores_gemma":[0.9993561,0.00003351296,0.00002465699,0.0001258502,0.0002386759,0.0002211848],"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":[0.000003048671,0.000003499078,0.00009025897,0.000007265412,0.00001453028,0.000008007077,0.0000456308,0.9956679,0.0001744685,0.0002802961,0.0002331631,0.003471879],"study_design_scores_gemma":[0.0002313131,0.00002379243,0.002437545,0.00003063575,0.000004052936,0.000006802253,0.00001514301,0.9849862,0.0003720994,0.000316168,0.01139716,0.0001790436],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1536301,0.0001744749,0.8157306,0.0004701648,0.0007265778,0.00009554757,0.00006982838,0.0002374154,0.02886532],"genre_scores_gemma":[0.9742989,0.0001178539,0.02474437,0.00009440474,0.0001195157,0.0000161715,0.00009283215,0.00001679948,0.0004991482],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8206688,"threshold_uncertainty_score":0.6585784,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01142726916525246,"score_gpt":0.2404927219074589,"score_spread":0.2290654527422064,"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."}}