{"id":"W2003180322","doi":"10.1002/elps.201000098","title":"Microfluidic devices for electrokinetic sample fractionation","year":2010,"lang":"en","type":"article","venue":"Electrophoresis","topic":"Microfluidic and Capillary Electrophoresis Applications","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada; National Institute for Nanotechnology; University of Alberta","funders":"","keywords":"Electrokinetic phenomena; Fractionation; Analyte; Microfluidics; Contamination; Chromatography; Sample (material); Throughput; Sample preparation; Materials science; Chip; Analytical Chemistry (journal); Nanotechnology; Chemistry; Computer science","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":[0.0001277847,0.00023249,0.0001968767,0.0001608237,0.000224667,0.00006062946,0.0002538994,0.0001650576,0.0005128995],"category_scores_gemma":[0.00006560014,0.000246248,0.0001234058,0.0003513113,0.00003969274,0.00009316848,0.000010456,0.0003185442,0.00008765042],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007998099,"about_ca_system_score_gemma":0.00005793061,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002354728,"about_ca_topic_score_gemma":0.0000363479,"domain_scores_codex":[0.9987152,0.00001354986,0.0002736853,0.0002971718,0.0001624531,0.0005378938],"domain_scores_gemma":[0.9992245,0.000173728,0.0000429246,0.000337531,0.0001176222,0.0001036766],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001401105,0.00001996963,0.00007807046,0.00001918175,0.00004102895,2.04143e-7,0.00001295068,0.000001395816,0.7738639,0.006070708,0.2174195,0.002459107],"study_design_scores_gemma":[0.0001659954,0.00005444376,0.001494066,0.000001858725,0.00003292748,0.000009831392,0.000006127843,0.0002647862,0.4734766,0.001979135,0.5223158,0.0001984118],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7759937,0.1143482,0.103245,0.0005477627,0.00062106,0.001248423,0.0001213909,0.001086126,0.002788238],"genre_scores_gemma":[0.9151186,0.08128748,0.001829781,0.0001638838,0.0005038419,0.0005897917,0.0002264195,0.0001079732,0.000172202],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3048964,"threshold_uncertainty_score":0.999999,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004614153332405842,"score_gpt":0.2094999156149329,"score_spread":0.2048857622825271,"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."}}