{"id":"W1919108253","doi":"10.1016/j.petrol.2015.10.035","title":"CO2 microbubbles – A potential fluid for enhanced oil recovery: Bulk and porous media studies","year":2015,"lang":"en","type":"article","venue":"Journal of Petroleum Science and Engineering","topic":"Drilling and Well Engineering","field":"Engineering","cited_by":75,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; Carbon Management Canada; University of Alberta","keywords":"Microbubbles; Enhanced oil recovery; Materials science; Porous medium; Rheology; Viscosity; Nanofluid; Pulmonary surfactant; Porosity; Petroleum engineering; Chemical engineering; Nanotechnology; Composite material; Ultrasound; Nanoparticle; Geology","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":[0.0009734413,0.0001739363,0.0003166512,0.0003314065,0.00006753432,0.0001041075,0.0001575291,0.00004835724,4.17577e-7],"category_scores_gemma":[0.0004222348,0.0001546552,0.00004428951,0.000209335,0.00008638742,0.0004843043,0.00003854801,0.0001496854,7.489598e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001155343,"about_ca_system_score_gemma":0.00006544547,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001800549,"about_ca_topic_score_gemma":0.000001143951,"domain_scores_codex":[0.9988798,0.00000334736,0.0003166134,0.000139823,0.0003154736,0.0003448874],"domain_scores_gemma":[0.9992487,0.00008076031,0.0000565603,0.00008558408,0.0002727439,0.0002556716],"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":[0.00001446278,0.000004405087,0.000004618119,0.0001231332,0.00004548965,0.000009667874,0.0005399486,0.7509152,0.2435755,0.00002854054,0.000262649,0.004476362],"study_design_scores_gemma":[0.002329313,0.0004809827,0.0002103443,0.0006567539,0.0001378938,0.0007772705,0.001409957,0.9094059,0.07481378,0.0001973372,0.00883438,0.000746069],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9391361,0.01144955,0.04714395,0.00009726397,0.001986356,0.00002681252,0.000005103214,0.00008142758,0.00007340292],"genre_scores_gemma":[0.9892999,0.002601446,0.007647299,0.00001418391,0.0003792964,0.000003652916,5.516214e-7,0.00002623408,0.00002745978],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1687617,"threshold_uncertainty_score":0.6306655,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01319770841929218,"score_gpt":0.2163658397823464,"score_spread":0.2031681313630542,"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."}}