{"id":"W4321783891","doi":"10.1016/j.petlm.2023.02.002","title":"Surfactant and nanoparticle synergy: Towards improved foam stability","year":2023,"lang":"en","type":"article","venue":"Petroleum","topic":"Pickering emulsions and particle stabilization","field":"Materials Science","cited_by":46,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Regina","funders":"Mitacs; Petroleum Technology Research Centre","keywords":"Pulmonary surfactant; Micromodel; Enhanced oil recovery; Materials science; Nanoparticle; Chemical engineering; Porous medium; Bubble; Foaming agent; Porosity; Pressure drop; Composite material; Nanotechnology","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":[0.0005263889,0.00009680263,0.0001331095,0.00003744592,0.0001478045,0.00007932087,0.00009490633,0.00003585064,0.0002220222],"category_scores_gemma":[0.000171499,0.00008196197,0.00002634029,0.0002119227,0.00007880441,0.000165643,0.0001186969,0.00004417013,0.0001654789],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003234049,"about_ca_system_score_gemma":0.0000338452,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001673887,"about_ca_topic_score_gemma":0.00007857837,"domain_scores_codex":[0.9989786,0.00006476439,0.0001901992,0.0002828332,0.000154516,0.0003291033],"domain_scores_gemma":[0.9994766,0.00006052898,0.00004016523,0.0002658382,0.00004270698,0.0001142038],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00002279682,0.0000279221,0.006003746,0.00001919252,0.000002044708,0.00000237833,0.000228308,0.0001297369,0.9918813,0.0002097056,0.0000680528,0.00140487],"study_design_scores_gemma":[0.0004649028,0.0001293629,0.09979589,0.00001182322,0.00001186854,0.000003791886,0.0002586436,0.08416677,0.8122383,0.0006391216,0.002070908,0.0002086028],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9983972,0.00004301298,0.0001780312,0.0004230105,0.0002536266,0.0000749216,0.00002594633,0.0003016843,0.0003025851],"genre_scores_gemma":[0.9995037,0.00001608126,0.0002030913,0.00003005407,0.00002897676,0.00002143923,0.000005315996,0.00001268957,0.0001786631],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1796429,"threshold_uncertainty_score":0.3342312,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02425878588880323,"score_gpt":0.2549759157572083,"score_spread":0.2307171298684051,"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."}}