{"id":"W4392774900","doi":"10.4043/34752-ms","title":"Smart Water Flood in Carbonate Reservoirs: an Integrated Analysis Through Zeta Potentiometric and Simulation Studies","year":2024,"lang":"en","type":"article","venue":"Offshore Technology Conference Asia","topic":"Enhanced Oil Recovery Techniques","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Potentiometric titration; Carbonate; Flood myth; Zeta potential; Computer science; Environmental science; Petroleum engineering; Geology; Materials science; Chemistry; Electrode; Nanotechnology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001800567,0.0001993965,0.0002166137,0.0002688622,0.0001517987,0.0002585469,0.0002214873,0.0003241938,0.0005775187],"category_scores_gemma":[0.0003282108,0.0001076887,0.0003450681,0.0002530676,0.0001508993,0.0002930648,0.0002079856,0.000239816,0.00006956117],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002888299,"about_ca_system_score_gemma":0.000229045,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004511938,"about_ca_topic_score_gemma":0.002456818,"domain_scores_codex":[0.9999546,0.000006916491,0.000003412596,0.00000742046,0.00001853634,0.000009076803],"domain_scores_gemma":[0.9998857,0.00005635045,0.0000148261,0.000009829047,0.00002691058,0.000006450512],"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":[0.0002923768,0.000269552,0.02707004,0.0002587019,0.00006860372,0.0005077416,0.0002288124,0.7668642,0.1841346,0.001675108,0.0004290043,0.0182013],"study_design_scores_gemma":[0.0000125292,0.0001836211,0.00500352,0.000003427515,0.00001328429,0.00003447731,0.00007766204,0.9562185,0.0378352,0.0002043295,0.0003987406,0.0000146343],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9941497,0.00004401888,0.004453842,0.00004461675,0.000003335143,0.0000164843,0.0001493794,0.00006191853,0.001076775],"genre_scores_gemma":[0.9985679,0.00004685936,0.001093462,0.000003646973,8.521341e-7,0.00001014674,0.00005448543,0.000003818509,0.0002188225],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004511938,"threshold_uncertainty_score":0.008971393,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02787599821997236,"score_gpt":0.3062893477452641,"score_spread":0.2784133495252917,"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."}}