{"id":"W1964402997","doi":"10.1115/icnmm2011-58151","title":"A Novel Scanning Molecular Tagging Velocimetry Technique for Two Dimensional Microfluidic Applications","year":2011,"lang":"en","type":"article","venue":"","topic":"Microfluidic and Capillary Electrophoresis Applications","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Microscale chemistry; Particle tracking velocimetry; Velocimetry; Particle image velocimetry; Microfluidics; Flow (mathematics); Shadowgraphy; Fluid dynamics; Flow visualization; Tracking (education); Microchannel; Flow velocity; Displacement (psychology); Fluidics; Optics; Computer science; Physics; Turbulence; Laser; Mechanics; Materials science; Nanotechnology; Aerospace engineering; Engineering","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":[0.000587281,0.0007916428,0.0005053058,0.0008750311,0.0004716264,0.0008964323,0.0009341803,0.001139955,0.001447505],"category_scores_gemma":[0.0005794896,0.0003983948,0.0004418473,0.0007019014,0.0004852606,0.0008625695,0.0006728204,0.00118232,0.00107332],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000586915,"about_ca_system_score_gemma":0.001022479,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00046414,"about_ca_topic_score_gemma":0.0005218989,"domain_scores_codex":[0.9994293,0.00005462164,0.00003343323,0.0001078037,0.0003286155,0.00004623083],"domain_scores_gemma":[0.9997439,0.00006099444,0.00006768398,0.00003200203,0.00006575885,0.00002960947],"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":[0.00003760513,0.00003440759,0.0001454462,0.0001301124,0.00000572087,0.0001048545,0.00003942931,0.0004951457,0.9433774,0.005593247,0.001377139,0.04865947],"study_design_scores_gemma":[0.00003013228,0.0003999524,0.0006067221,0.00003092189,0.00002465929,0.0008783565,0.00001742862,0.02493693,0.9051853,0.0008462291,0.06698213,0.00006105148],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.05757043,0.005750341,0.9230581,0.001019249,0.001077277,0.0005017282,0.0003238043,0.003133524,0.007565505],"genre_scores_gemma":[0.2391002,0.004761693,0.7421108,0.0006092301,0.0002883908,0.0008171463,0.0005716069,0.0001550387,0.01158589],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.001447505,"threshold_uncertainty_score":0.004842341,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01174098732094099,"score_gpt":0.2247395597163885,"score_spread":0.2129985723954475,"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."}}