{"id":"W2086471142","doi":"10.1007/s10404-008-0320-6","title":"A Y-channel design for improving zeta potential and surface conductivity measurements using the current monitoring method","year":2008,"lang":"en","type":"article","venue":"Microfluidics and Nanofluidics","topic":"Microfluidic and Capillary Electrophoresis Applications","field":"Engineering","cited_by":27,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Zeta potential; Conductivity; Current (fluid); Materials science; Conductance; Electrolysis; Microfluidics; Analytical Chemistry (journal); Joule heating; Mechanics; Streaming current; Chemistry; Nanotechnology; Electrokinetic phenomena; Electrode; Thermodynamics; Composite material; Chromatography; Mathematics; Physics","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0007845616,0.000357394,0.0003410157,0.00007356179,0.0009410052,0.00008457498,0.000201943,0.0001315485,0.000002328625],"category_scores_gemma":[0.00002411075,0.0003077394,0.00009622177,0.0002230442,0.0001562063,0.0001491073,0.00007364765,0.000266091,0.000001156697],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009617719,"about_ca_system_score_gemma":0.0001015356,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003724432,"about_ca_topic_score_gemma":1.764313e-7,"domain_scores_codex":[0.9983017,0.0001057743,0.0003827215,0.0004355442,0.0002430049,0.0005311828],"domain_scores_gemma":[0.9991668,0.0001253575,0.00007494328,0.0003187153,0.0001590999,0.0001551145],"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":[0.00002336463,0.00002718831,0.0001166085,0.00008757035,0.0000748141,0.000001705916,0.0002796984,0.0001275183,0.9893819,0.0000315025,0.004752033,0.005096102],"study_design_scores_gemma":[0.0006098505,0.00006229882,0.0001380077,0.00002892364,0.0001699358,0.0001479703,0.0000918488,0.01154538,0.9770734,0.0002057824,0.009523835,0.0004027312],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.374167,0.2275402,0.3974671,0.00002929379,0.0002531876,0.0004549782,0.00002251826,0.00006275567,0.000003078167],"genre_scores_gemma":[0.7707046,0.2222313,0.006573168,0.00002861487,0.0002665583,0.00006687615,0.00001037396,0.00009674285,0.00002174799],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.3965376,"threshold_uncertainty_score":0.9999375,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0700115752620797,"score_gpt":0.2759446895517585,"score_spread":0.2059331142896788,"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."}}