{"id":"W4255926116","doi":"10.26434/chemrxiv.11413191","title":"Visualization of Streams of Small Organic Molecules in Continuous-Flow Electrophoresis","year":2019,"lang":"en","type":"preprint","venue":"ChemRxiv","topic":"Microfluidic and Capillary Electrophoresis Applications","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Analyte; STREAMS; Visualization; Detection limit; Fluorescence; Inert; Continuous flow; Analytical Chemistry (journal); Free-flow electrophoresis; Microfluidics; Chemistry; Materials science; Chromatography; Nanotechnology; Computer science; Organic chemistry; Data mining; Mechanics; Optics; Physics","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":[0.0005701247,0.0004277069,0.0002761969,0.0004600322,0.0002406346,0.0008912681,0.0006356303,0.0008813248,0.0006760941],"category_scores_gemma":[0.0006695767,0.000294161,0.0002039486,0.0003429019,0.0007084774,0.0006929808,0.0005943817,0.0006849497,0.0003028582],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004509004,"about_ca_system_score_gemma":0.0002974904,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005506809,"about_ca_topic_score_gemma":0.000649692,"domain_scores_codex":[0.9996221,0.00007186862,0.00001807934,0.0001140797,0.0001160405,0.00005769659],"domain_scores_gemma":[0.9996087,0.0002395221,0.00004694825,0.00002416461,0.00004515904,0.00003557151],"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":[0.00004830346,0.00001785288,0.0001344974,0.0000655946,0.000003121885,0.00004283621,0.00002317674,0.0003407364,0.996107,0.0005662681,0.00006736931,0.002583267],"study_design_scores_gemma":[0.00001144907,0.00005287962,0.0005804299,0.000009969567,0.00000378432,0.00008497625,0.00001375605,0.005378186,0.9919074,0.0002182428,0.001727701,0.0000112761],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7046173,0.004146208,0.2848579,0.0003926682,0.0001634517,0.0002359421,0.0005961056,0.0005658182,0.004424713],"genre_scores_gemma":[0.79329,0.002573044,0.1991102,0.0002041586,0.00006504635,0.0002076491,0.0004392107,0.00006822679,0.004042479],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0008912681,"threshold_uncertainty_score":0.003271461,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0063753041510232,"score_gpt":0.2040816434814217,"score_spread":0.1977063393303986,"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."}}