{"id":"W2475316316","doi":"10.1002/jssc.201600350","title":"Model‐based analysis of a dielectrophoretic microfluidic device for field‐flow fractionation","year":2016,"lang":"en","type":"article","venue":"Journal of Separation Science","topic":"Microfluidic and Bio-sensing Technologies","field":"Engineering","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"Al Jalila Foundation; Utah Agricultural Experiment Station","keywords":"Microchannel; Levitation; Mechanics; Dielectrophoresis; Drag; Microfluidics; Volumetric flow rate; Microparticle; Voltage; Steady state (chemistry); RADIUS; Materials science; Chemistry; Physics; Optics; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004238125,0.00005789609,0.0001498341,0.0005927291,0.00005441926,0.00001963326,0.0001660114,0.00004905494,0.00000962321],"category_scores_gemma":[0.000232903,0.00003855069,0.0000888806,0.0008871811,0.00009112249,0.0002683898,0.00000711396,0.00004536466,8.183809e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009346196,"about_ca_system_score_gemma":0.0001135664,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001043193,"about_ca_topic_score_gemma":0.000001451986,"domain_scores_codex":[0.9992673,0.000006124754,0.0003034637,0.00007932051,0.0002349985,0.0001088318],"domain_scores_gemma":[0.9991341,0.0001265067,0.0001586318,0.0001043974,0.0004497398,0.00002668476],"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":[0.00001869416,0.000008827496,0.00009078228,0.00000540464,0.0000302879,2.05788e-7,0.00003560509,0.01037525,0.980913,0.00009828177,0.002053006,0.00637068],"study_design_scores_gemma":[0.0001164557,0.00007094791,0.00025438,0.00001564969,0.00007576416,0.000001996318,0.000009828907,0.359827,0.6389405,0.0002669587,0.0003810054,0.00003954105],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3508974,0.0003526877,0.648252,0.0003454106,0.00006756467,0.00003489546,0.000003453902,0.00001666383,0.00002992843],"genre_scores_gemma":[0.9867408,0.0003605389,0.0128162,0.00004788274,0.00001604558,0.000001176039,5.986082e-7,0.000003140743,0.00001360111],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6358434,"threshold_uncertainty_score":0.1572051,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02399597514371893,"score_gpt":0.30253343806118,"score_spread":0.2785374629174611,"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."}}