{"id":"W2072631696","doi":"10.1016/j.chroma.2008.08.002","title":"Modeling wall effects in capillary electrochromatography","year":2008,"lang":"en","type":"article","venue":"Journal of Chromatography A","topic":"Microfluidic and Capillary Electrophoresis Applications","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Carleton University","funders":"","keywords":"Capillary electrochromatography; Electrochromatography; Chemistry; Porosity; Capillary action; Chromatography; Electro-osmosis; Zeta potential; Flow (mathematics); Packed bed; Mechanics; Capillary electrophoresis; Composite material; Electrophoresis; Materials science; Nanotechnology","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":[0.0004538666,0.0008431527,0.0004965882,0.000322312,0.0004075951,0.001200071,0.001121454,0.002188291,0.001290132],"category_scores_gemma":[0.002215221,0.0006481928,0.0004400159,0.0003563997,0.0005127606,0.001255867,0.0005476662,0.0006829521,0.0003802726],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009412491,"about_ca_system_score_gemma":0.000841355,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009088077,"about_ca_topic_score_gemma":0.004246782,"domain_scores_codex":[0.999749,0.00006933186,0.000007882577,0.0000358702,0.00008304531,0.00005488687],"domain_scores_gemma":[0.999273,0.0004930667,0.00005363842,0.00003915216,0.0001028156,0.00003832539],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00005212229,0.0001207277,0.0005270671,0.00007026233,0.00002132603,0.0002217553,0.00005049327,0.9414037,0.03405258,0.01628054,0.0005317751,0.006667668],"study_design_scores_gemma":[0.00000389617,0.000006589045,0.00007249218,0.000002806132,0.000004442646,0.000005198493,0.000003275108,0.9954749,0.003814838,0.0004609224,0.0001465992,0.000004024704],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5060723,0.002202685,0.4564497,0.0008267399,0.0003092279,0.000159866,0.000179,0.0007865306,0.03301387],"genre_scores_gemma":[0.9739453,0.0007258019,0.01528107,0.00009827612,0.00002975721,0.0000627242,0.00006789849,0.000134129,0.00965521],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009088077,"threshold_uncertainty_score":0.01807034,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005346257040905216,"score_gpt":0.1868325693941227,"score_spread":0.1814863123532174,"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."}}