{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00004930338,0.0001831175,0.0002396013,0.00009058849,0.0000560355,0.00001829817,0.0001764457,0.0001146549,0.00002530274],"category_scores_gemma":[0.00006630983,0.0001498473,0.000080611,0.0003551252,0.0000646204,0.00002946212,0.00003069129,0.0002098225,0.00005154956],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005221011,"about_ca_system_score_gemma":0.00001605181,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006632845,"about_ca_topic_score_gemma":0.000001284222,"domain_scores_codex":[0.9991031,0.000008351172,0.000221945,0.0001968613,0.0001422975,0.0003274706],"domain_scores_gemma":[0.9996143,0.00004716003,0.0000328434,0.0002234338,0.000022381,0.00005990213],"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":[0.00009285734,0.00002445318,0.0000910698,0.00003494303,0.00003725401,0.00001451336,0.00007971278,0.00005820534,0.9760844,0.0005615982,0.01125033,0.01167073],"study_design_scores_gemma":[0.0002231301,0.0003609379,0.001051231,0.00004111421,0.00001741004,0.000004949615,0.00003667771,0.0005192292,0.9945566,0.0002504468,0.002764748,0.0001735292],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9963334,0.00113465,0.0004249082,0.0005894516,0.00005526821,0.00009449184,0.000008858967,0.0006348091,0.0007242066],"genre_scores_gemma":[0.9982941,0.0003810089,0.0009885267,0.0002108535,0.00006631683,0.00000261283,0.000003616939,0.00003564306,0.00001729901],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01847227,"threshold_uncertainty_score":0.6110595,"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."}}