{"id":"W4405089684","doi":"10.1063/5.0241606","title":"Rheology and magnetorheology of ferrofluid emulsions: Insights into formulation and stability","year":2024,"lang":"en","type":"article","venue":"Physics of Fluids","topic":"Pickering emulsions and particle stabilization","field":"Materials Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; Ministerio de Ciencia, Tecnología e Innovación","keywords":"Ferrofluid; Emulsion; Pulmonary surfactant; Rheology; Chemical engineering; Viscosity; Nanoparticle; Surface tension; Ethylene oxide; Materials science; Chromatography; Chemistry; Thermodynamics; Composite material; Nanotechnology; Magnetic field; Polymer; Physics; Copolymer","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003174589,0.0003131098,0.0001947078,0.0002801105,0.0000789862,0.0003159883,0.0001164019,0.0002587299,0.0004227948],"category_scores_gemma":[0.0003712396,0.0001118498,0.0001370386,0.0001306458,0.0002186736,0.0003447871,0.0001276598,0.0003299992,0.0001455265],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001920198,"about_ca_system_score_gemma":0.0001566803,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003411612,"about_ca_topic_score_gemma":0.0003191294,"domain_scores_codex":[0.9999175,0.00001825868,0.000008024679,0.00001926152,0.00002188965,0.00001507454],"domain_scores_gemma":[0.9998817,0.0000341043,0.00003776705,0.000006282718,0.00002868757,0.00001129839],"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":[0.00002965284,0.00000973187,0.0003257801,0.00003854973,0.000003032564,0.00003841024,0.00001522556,0.00009591491,0.9975553,0.00004605174,0.000009806392,0.001832601],"study_design_scores_gemma":[0.000007101554,0.0001612553,0.005345699,0.00001500866,0.0000145042,0.0001855799,0.00004660389,0.002792992,0.9904624,0.0001319308,0.000827821,0.000009065449],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9722859,0.00828574,0.01748596,0.0001954255,0.00003073921,0.00002851814,0.0001334801,0.00009328585,0.001460874],"genre_scores_gemma":[0.9926993,0.002686995,0.003708717,0.00004356081,0.0000139407,0.00001291347,0.00006754453,0.00002081787,0.0007461411],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0004227948,"threshold_uncertainty_score":0.001678884,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0203811885545033,"score_gpt":0.2721091645686899,"score_spread":0.2517279760141866,"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."}}