{"id":"W2735214340","doi":"10.1021/acs.iecr.7b01675","title":"Silica Nanoparticle Enhancement in the Efficiency of Surfactant Flooding of Heavy Oil in a Glass Micromodel","year":2017,"lang":"en","type":"article","venue":"Industrial & Engineering Chemistry Research","topic":"Enhanced Oil Recovery Techniques","field":"Engineering","cited_by":90,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"European Regional Development Fund; Islamic Azad University; Llywodraeth Cymru; Islamic Azad University, Central Tehran Branch; Welch Foundation","keywords":"Micromodel; Pulmonary surfactant; Fumed silica; Enhanced oil recovery; Chemical engineering; Sodium dodecyl sulfate; Wetting; Nanoparticle; Materials science; Contact angle; Chemistry; Chromatography; Nanotechnology; Composite material; Porosity; Porous medium","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":[0.0002137911,0.0004432554,0.000235947,0.0001813334,0.0001077253,0.0001861411,0.0002817666,0.0003281398,0.0006815425],"category_scores_gemma":[0.0001770935,0.0001678159,0.0002976782,0.0001277968,0.0001777802,0.0002833409,0.0002681983,0.0002167271,0.0002307297],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003029012,"about_ca_system_score_gemma":0.0002798746,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001591196,"about_ca_topic_score_gemma":0.002853332,"domain_scores_codex":[0.9998536,0.00001416709,0.00001158879,0.00004489229,0.00004301949,0.00003275948],"domain_scores_gemma":[0.9998978,0.00003132772,0.00003194359,0.000008567341,0.00001597542,0.00001428385],"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":[0.00001701363,0.00000337452,0.00004311388,0.000008854079,8.846268e-7,0.000008551596,0.000005987845,0.00005688488,0.9995757,0.000009576254,0.000003895054,0.0002661826],"study_design_scores_gemma":[0.000001573056,0.00008056899,0.0003804531,7.939829e-7,0.000002780596,0.000008592403,0.000004948183,0.0006959942,0.998675,0.00000355563,0.0001440326,0.000001690615],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9950245,0.0002599373,0.003810835,0.00002752182,0.000008938316,0.000022704,0.0001192772,0.0001494881,0.000576772],"genre_scores_gemma":[0.9898707,0.0003653341,0.008115843,0.00001828888,0.000003619163,0.0000297504,0.0001493188,0.00002322576,0.001423791],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001591196,"threshold_uncertainty_score":0.003163874,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07685950884708137,"score_gpt":0.331209308244349,"score_spread":0.2543497993972677,"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."}}