{"id":"W2045363318","doi":"10.1103/physreve.81.056318","title":"Magnetic resonance imaging of two-component liquid-liquid flow in a circular capillary tube","year":2010,"lang":"en","type":"article","venue":"Physical Review E","topic":"Innovative Microfluidic and Catalytic Techniques Innovation","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of New Brunswick","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Hagen–Poiseuille equation; Capillary action; RADIUS; Microfluidics; Flow (mathematics); Nuclear magnetic resonance; Tube (container); Materials science; Physics; Resolution (logic); Resonance (particle physics); Mechanics; Analytical Chemistry (journal); Optics; Chemistry; Atomic physics; Thermodynamics; Chromatography","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":[0.0001593506,0.0002049398,0.0001619042,0.0003645664,0.0001854705,0.0002134082,0.0002503593,0.0003497889,0.0004806389],"category_scores_gemma":[0.0002616731,0.00010962,0.00008114844,0.0001710511,0.0003852777,0.0002740133,0.000203963,0.0001862426,0.00009110074],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002286185,"about_ca_system_score_gemma":0.000245512,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000549442,"about_ca_topic_score_gemma":0.0004217057,"domain_scores_codex":[0.9999543,0.000007141802,0.000001382057,0.00001593371,0.0000124425,0.000008714866],"domain_scores_gemma":[0.9998689,0.00005915321,0.00002462063,0.000005201613,0.0000188984,0.0000230766],"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":[0.00008276197,0.00001481588,0.000296746,0.00002910809,0.000002656665,0.0001544502,0.00002444011,0.000257332,0.9957509,0.0003944222,0.0000365355,0.002955798],"study_design_scores_gemma":[0.0000420893,0.0006032755,0.005826779,0.000009961729,0.00002137219,0.000932832,0.00004979031,0.02561,0.965114,0.0002819415,0.001484741,0.00002318094],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9604844,0.0009851984,0.03656647,0.0001158321,0.00001463574,0.00003362055,0.00005262056,0.0001828591,0.001564233],"genre_scores_gemma":[0.9695863,0.0004423189,0.02877314,0.00003689537,0.00001345312,0.00003153524,0.00003625197,0.00000984443,0.00107042],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.000549442,"threshold_uncertainty_score":0.001658738,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008414573411580407,"score_gpt":0.2601957494055059,"score_spread":0.2517811759939255,"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."}}