{"id":"W2765394769","doi":"10.1038/s41598-017-13090-z","title":"Semi-Empirical Estimation of Dean Flow Velocity in Curved Microchannels","year":2017,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Microfluidic and Bio-sensing Technologies","field":"Engineering","cited_by":34,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"Ministry of Environment; Government of Ontario","keywords":"Microfluidics; Mechanics; Spiral (railway); Sorting; Displacement (psychology); Vortex; Materials science; Flow (mathematics); Hydraulic diameter; Flow velocity; Microchannel; Physics; Nanotechnology; Computer science; Mechanical engineering; Reynolds number; Engineering; Turbulence","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":[0.001038413,0.0004559327,0.0003758241,0.001482102,0.0002161544,0.0005382003,0.0006031544,0.0004509614,0.0003978473],"category_scores_gemma":[0.005211585,0.0002326799,0.0003542948,0.0006063345,0.0006375858,0.0009834175,0.0005576775,0.0003394885,0.0001816767],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005210407,"about_ca_system_score_gemma":0.0007563373,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001453992,"about_ca_topic_score_gemma":0.001017117,"domain_scores_codex":[0.9995962,0.0001007358,0.00003194313,0.0001123015,0.0001104429,0.0000484379],"domain_scores_gemma":[0.9979795,0.00108073,0.0003917955,0.0002194823,0.0002628267,0.00006579647],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002690581,0.0001365219,0.03729332,0.0003139898,0.00006760076,0.0003548214,0.0003138048,0.7332469,0.09651771,0.02796831,0.0008697308,0.1026482],"study_design_scores_gemma":[0.00000379647,0.00002725046,0.003444857,0.00001178226,0.000004511422,0.00008649753,0.00001988906,0.9831573,0.011275,0.001484642,0.0004567022,0.0000277652],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2095725,0.0004578363,0.7874728,0.0000501407,0.0000199091,0.00008288633,0.0001681036,0.0006112264,0.001564635],"genre_scores_gemma":[0.9027507,0.0003222553,0.0960684,0.00001759057,0.000009819783,0.00007737608,0.0001646015,0.00004624344,0.0005430608],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001482102,"threshold_uncertainty_score":0.005491734,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02650600418487616,"score_gpt":0.267794837032407,"score_spread":0.2412888328475308,"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."}}