{"id":"W2034129327","doi":"10.1063/1.4722000","title":"Optimization of an electrokinetic mixer for microfluidic applications","year":2012,"lang":"en","type":"article","venue":"Biomicrofluidics","topic":"Microfluidic and Capillary Electrophoresis Applications","field":"Engineering","cited_by":29,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Micromixer; Electrokinetic phenomena; Waveform; Microfluidics; Mixing (physics); Microchannel; Mechanics; Flow (mathematics); Acoustics; Amplitude; Materials science; Electronic engineering; Computer science; Physics; Engineering; Optics; Electrical engineering; Voltage; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004698909,0.0005725321,0.0003990731,0.0002502774,0.0002213948,0.0006328871,0.0002967536,0.0005413716,0.0006935087],"category_scores_gemma":[0.0006239563,0.0002992518,0.0002385124,0.0002105495,0.0002898882,0.0003719777,0.0003559693,0.0004092812,0.0002998544],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003680287,"about_ca_system_score_gemma":0.0004515822,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001247197,"about_ca_topic_score_gemma":0.0002624855,"domain_scores_codex":[0.999846,0.00002201419,0.0000102768,0.00003261452,0.00006974392,0.00001933969],"domain_scores_gemma":[0.9998385,0.0000774006,0.00003991315,0.00001231127,0.00002248146,0.000009389347],"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":[0.0001089513,0.0001155475,0.0003804245,0.0002248059,0.00001962428,0.00006376841,0.00003848004,0.1940544,0.7807716,0.003733523,0.0001445754,0.0203442],"study_design_scores_gemma":[0.0000662633,0.0005522071,0.001079512,0.0000240514,0.00004245472,0.0001146433,0.00003177705,0.4987784,0.4931673,0.001144624,0.0049693,0.00002948649],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.4360043,0.001033087,0.5551234,0.0002983971,0.00006022663,0.0001782782,0.0001085517,0.0002759229,0.006917914],"genre_scores_gemma":[0.7803383,0.0006458846,0.2164964,0.00004212874,0.00001759822,0.0001996629,0.00008590468,0.00005379008,0.002120316],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.0006935087,"threshold_uncertainty_score":0.002670228,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008294539392689664,"score_gpt":0.2210067173302624,"score_spread":0.2127121779375727,"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."}}