{"id":"W4313531670","doi":"10.1016/j.colsurfa.2022.130911","title":"Impact dynamics of ferrofluid droplet on a PDMS substrate under the influence of magnetic field","year":2023,"lang":"en","type":"article","venue":"Colloids and Surfaces A Physicochemical and Engineering Aspects","topic":"Fluid Dynamics and Heat Transfer","field":"Engineering","cited_by":36,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; Indian Institute of Technology Guwahati; Department of Scientific and Industrial Research, Ministry of Science and Technology, India","keywords":"Ferrofluid; Magnetic field; Materials science; Perpendicular; Magnetic nanoparticles; Mechanics; Chemical physics; Condensed matter physics; Nanotechnology; Nanoparticle; Chemistry; Physics; Geometry","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":[0.00005205178,0.0001621279,0.000235458,0.00004952178,0.00002659451,0.00001900235,0.0000841602,0.00006671933,0.000003455822],"category_scores_gemma":[0.000007890583,0.000120585,0.00005708337,0.000290773,0.00005363052,0.00003775227,0.00002358929,0.0001473979,9.904534e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001660935,"about_ca_system_score_gemma":0.000009421976,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005412779,"about_ca_topic_score_gemma":0.000009620348,"domain_scores_codex":[0.9993807,0.000004088936,0.0001663565,0.0001297416,0.0001119779,0.0002071517],"domain_scores_gemma":[0.999613,0.0001510726,0.000009509201,0.0001374837,0.00002358716,0.00006537293],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001538336,0.00001720201,0.0004692946,0.0002145284,0.00004264733,0.000001743584,0.0001247006,0.3995829,0.5940406,0.005266197,0.00004848997,0.0001763039],"study_design_scores_gemma":[0.0003504565,0.0003138224,0.1035546,0.0001495299,0.00002767475,0.000003216829,0.00006731968,0.8704814,0.02391607,0.0008960039,0.000009308986,0.0002306268],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9990019,0.0004249352,0.0001018777,0.00008215801,0.00003976816,0.00008975949,0.00003684836,0.00007814699,0.0001446517],"genre_scores_gemma":[0.9993064,0.000598677,0.00002222893,0.000009262279,0.00001422131,0.000006164229,0.000007786225,0.00002090027,0.00001430392],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5701246,"threshold_uncertainty_score":0.4917313,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005011580761082844,"score_gpt":0.2003724262793415,"score_spread":0.1953608455182587,"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."}}