{"id":"W1966084286","doi":"10.1039/b808236g","title":"New advances in on-line sample preconcentration by capillary electrophoresis using dynamic pH junction","year":2008,"lang":"en","type":"article","venue":"The Analyst","topic":"Microfluidic and Capillary Electrophoresis Applications","field":"Engineering","cited_by":51,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Electrokinetic phenomena; Capillary electrophoresis; Capillary action; Chromatography; Electrophoresis; Sample (material); Chemistry; Analytical Chemistry (journal); TRACE (psycholinguistics); Line (geometry); Sample preparation; Sensitivity (control systems); Ionic bonding; Materials science; Nanotechnology; Ion","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00238751,0.0005863925,0.0006148243,0.0007772612,0.0002088608,0.001195447,0.00133432,0.0008960479,0.001126084],"category_scores_gemma":[0.001359166,0.0004111743,0.0003983099,0.0005636759,0.0006935684,0.001855773,0.0007280039,0.001343338,0.0004594055],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004678143,"about_ca_system_score_gemma":0.000538366,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003393807,"about_ca_topic_score_gemma":0.0005656176,"domain_scores_codex":[0.9990829,0.0001842648,0.00005434758,0.0002218393,0.000401875,0.00005478355],"domain_scores_gemma":[0.9989735,0.0004614015,0.000116033,0.00009072918,0.0002765681,0.00008186847],"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":[0.0001854455,0.0002515936,0.001384785,0.001177476,0.00005984214,0.0002154415,0.0002713038,0.001027095,0.7224292,0.01743365,0.001566719,0.2539975],"study_design_scores_gemma":[0.00003798456,0.0009083342,0.002348997,0.00009351978,0.0001249531,0.002246751,0.0001411004,0.01203521,0.8510366,0.003282115,0.127627,0.000117437],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.243811,0.2716804,0.4526715,0.005498463,0.0009697167,0.0003190099,0.000299166,0.001326035,0.02342476],"genre_scores_gemma":[0.3989249,0.1526467,0.4354046,0.002151277,0.0009117849,0.000150324,0.0003712719,0.0001821425,0.009257107],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00238751,"threshold_uncertainty_score":0.01262653,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009954634660733413,"score_gpt":0.2272497101641358,"score_spread":0.2172950755034024,"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."}}