{"id":"W1998258490","doi":"10.1039/c3lc50401h","title":"Multiplexed electrokinetic sample fractionation, preconcentration and elution for proteomics","year":2013,"lang":"en","type":"article","venue":"Lab on a Chip","topic":"Microfluidic and Bio-sensing Technologies","field":"Engineering","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada; National Institute for Nanotechnology; University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; University of Alberta","keywords":"Electrokinetic phenomena; Chromatography; Fractionation; Elution; Chemistry; Proteomics; Sample preparation; Multiplexing; Computer science; Biochemistry","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":[0.00003630663,0.00007041817,0.00005923344,0.00003573567,0.0000490554,0.00003140089,0.00003006281,0.00007621719,0.0000201405],"category_scores_gemma":[0.0001026434,0.00006476458,0.00001336617,0.00004455826,0.00001681704,0.00007297079,0.000004563846,0.00006343966,0.00001448449],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004090746,"about_ca_system_score_gemma":0.000005295754,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000176193,"about_ca_topic_score_gemma":0.000005689304,"domain_scores_codex":[0.9996523,0.000005323147,0.00009062596,0.00009568343,0.00003903721,0.0001170063],"domain_scores_gemma":[0.999803,0.00005463004,0.00001925996,0.00007519904,0.00003227194,0.00001565753],"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":[0.00001028273,0.00001378845,0.000315802,0.00003104052,0.000009842697,3.373764e-8,0.0000547463,0.0001356786,0.9695113,0.002588925,0.004063324,0.02326521],"study_design_scores_gemma":[0.0006330615,0.0001360563,0.01418694,0.00002578965,0.00000951231,0.000003860799,0.00005354005,0.08292673,0.8810828,0.01064257,0.01009557,0.0002035341],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9339308,0.0001706742,0.06379955,0.0005088475,0.0001093111,0.0007990903,0.00001420218,0.0005112452,0.0001562608],"genre_scores_gemma":[0.9777744,0.0001171341,0.0218413,0.0000448881,0.00004737488,0.00008758372,0.00003796108,0.00001109725,0.00003827995],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08842848,"threshold_uncertainty_score":0.2641023,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00868824499247718,"score_gpt":0.1928533564808877,"score_spread":0.1841651114884106,"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."}}