{"id":"W1990072453","doi":"10.1115/1.4001292","title":"Experimental Analysis of Microchannel Entrance Length Characteristics Using Microparticle Image Velocimetry","year":2010,"lang":"en","type":"article","venue":"Journal of Fluids Engineering","topic":"Heat Transfer and Optimization","field":"Engineering","cited_by":59,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"Natural Sciences and Engineering Research Council of Canada; Concordia University","keywords":"Microchannel; Laminar flow; Reynolds number; Particle image velocimetry; Mechanics; Hydraulic diameter; Velocimetry; Flow conditioning; Flow (mathematics); Materials science; Optics; Physics; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001668969,0.0001394369,0.0003522253,0.0003724797,0.00002138587,0.00002619565,0.0001293197,0.00007163458,0.00004939909],"category_scores_gemma":[0.00002341732,0.0001459272,0.0001769328,0.0004970613,0.00001952334,0.0002329772,0.000008426576,0.000259457,9.241357e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004569413,"about_ca_system_score_gemma":0.00001669628,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002627962,"about_ca_topic_score_gemma":3.785381e-7,"domain_scores_codex":[0.9990429,0.000006881692,0.000524718,0.00007184888,0.0001545932,0.0001991161],"domain_scores_gemma":[0.9996117,0.00002852087,0.00004080949,0.0001153484,0.0001021324,0.0001014846],"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":[0.000007870354,0.00003086969,0.0003841712,0.00004344156,0.0002497183,0.000008362054,0.0003795587,0.1404206,0.8583046,0.00001713002,0.000006455699,0.0001472657],"study_design_scores_gemma":[0.0001840226,0.00001835392,0.002794051,0.00002008254,0.0001977642,0.00002067882,0.00002722019,0.3997817,0.5968351,2.795184e-7,0.00002904313,0.00009172465],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6953722,0.0002655139,0.3038844,0.000003624255,0.0003986575,0.00002666405,0.00001037404,0.0000233528,0.00001517162],"genre_scores_gemma":[0.9607555,0.00004568329,0.03902375,0.000004508093,0.0001361971,5.352816e-7,0.000002652181,0.0000299989,0.000001157013],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2653833,"threshold_uncertainty_score":0.5950739,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006284348531257592,"score_gpt":0.2183928659144238,"score_spread":0.2121085173831662,"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."}}