{"id":"W2601010496","doi":"10.1002/elps.201600545","title":"Improved sensitivity by post‐column chemical environment modification of CE‐ESI‐MS using a flow‐through microvial interface","year":2017,"lang":"en","type":"article","venue":"Electrophoresis","topic":"Microfluidic and Capillary Electrophoresis Applications","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Chemistry; Analytical Chemistry (journal); Chromatography; Electrospray ionization; Mass spectrometry; Chemical modification; Capillary electrophoresis; Electrospray; Electrolyte; Ionization; Ion; Electrode; Organic chemistry","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":[0.001658384,0.001073636,0.0005248451,0.0003873465,0.0002420184,0.0006808109,0.0007214112,0.001131518,0.0009811999],"category_scores_gemma":[0.002468843,0.0005070345,0.0004296739,0.0002215036,0.0005121873,0.0008636013,0.0004775513,0.0009188294,0.0004400115],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003974006,"about_ca_system_score_gemma":0.0004844127,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006302588,"about_ca_topic_score_gemma":0.0008379091,"domain_scores_codex":[0.9989196,0.0002486983,0.00008961654,0.0002671845,0.0003534041,0.0001213921],"domain_scores_gemma":[0.9987711,0.0005322736,0.0001931813,0.00008557356,0.0003703552,0.00004731197],"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":[0.00003435042,0.00000872521,0.000121058,0.0000567962,0.000009523523,0.00002675723,0.00001464885,0.00003681468,0.9975578,0.00006462558,0.00002866452,0.002040249],"study_design_scores_gemma":[0.000004462097,0.00007569945,0.0009551683,0.000004381555,0.00001619388,0.0001900452,0.000006712867,0.000734776,0.9967945,0.0000403953,0.001168292,0.000009240065],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7749374,0.009385433,0.2098121,0.0007703956,0.0004959378,0.0003047892,0.0002593736,0.001358811,0.002675782],"genre_scores_gemma":[0.7898984,0.004016466,0.1999979,0.001104411,0.0001314686,0.0002651234,0.0005431696,0.0002475267,0.003795515],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001658384,"threshold_uncertainty_score":0.008770466,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008322173170014494,"score_gpt":0.2193169576813757,"score_spread":0.2109947845113612,"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."}}