{"id":"W3091889135","doi":"10.1002/elps.202000247","title":"Sheath‐assisted focusing of microparticles on lab‐on‐a‐chip platforms","year":2020,"lang":"en","type":"article","venue":"Electrophoresis","topic":"Microfluidic and Bio-sensing Technologies","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Okanagan University College; University of British Columbia, Okanagan Campus; Kelowna General Hospital; University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Microscale chemistry; Sorting; Aspect ratio (aeronautics); Volumetric flow rate; Multiphysics; Position (finance); Chip; Particle (ecology); Flow (mathematics); Microchannel; Mechanics; Standard deviation; Throughput; Materials science; Nanotechnology; Mechanical engineering; Computer science; Physics; Optoelectronics; Engineering; Algorithm; Mathematics; Finite element method; Thermodynamics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003834826,0.000338893,0.0003578622,0.0003063646,0.0001870768,0.0003462762,0.000664932,0.0004906953,0.0007644063],"category_scores_gemma":[0.0004711391,0.0001986657,0.0003540463,0.0002235476,0.000244108,0.0004052277,0.0002761832,0.0003797587,0.0003387995],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006020875,"about_ca_system_score_gemma":0.0004345818,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001290665,"about_ca_topic_score_gemma":0.001981113,"domain_scores_codex":[0.9998106,0.00002126986,0.000009424583,0.00002932935,0.00009979528,0.00002960308],"domain_scores_gemma":[0.9997699,0.0001038007,0.00003644417,0.00002233928,0.00005130437,0.00001631189],"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":[0.0000872107,0.0000848166,0.0005774684,0.0003495005,0.00003037178,0.0001999998,0.00009558548,0.04061074,0.9353936,0.003167841,0.001034896,0.01836797],"study_design_scores_gemma":[0.00002591295,0.000315105,0.000938486,0.00001652927,0.00002351175,0.00007977687,0.0000268643,0.2343158,0.7584898,0.0005627797,0.005166906,0.00003848783],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7021791,0.00240361,0.2861384,0.0002374931,0.0001586026,0.0001544909,0.0006089908,0.002787022,0.005332215],"genre_scores_gemma":[0.8800908,0.001521598,0.1155361,0.0001588606,0.00003619236,0.0001890562,0.000417139,0.00008945922,0.00196083],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001290665,"threshold_uncertainty_score":0.004368424,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0197081987876505,"score_gpt":0.1971556087679999,"score_spread":0.1774474099803494,"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."}}