{"id":"W2126686868","doi":"10.1016/s0021-9797(02)00181-9","title":"Visualization and numerical modelling of microfluidic on-chip injection processes","year":2003,"lang":"en","type":"article","venue":"Journal of Colloid and Interface Science","topic":"Microfluidic and Capillary Electrophoresis Applications","field":"Engineering","cited_by":43,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of New Brunswick; University of Toronto","funders":"","keywords":"Microfluidics; Laplace pressure; Meniscus; Microchannel; Visualization; Diffusion; Materials science; Analytical Chemistry (journal); Intersection (aeronautics); Mechanics; Sample (material); Electrophoresis; Chemistry; Pressure gradient; Chip; Laplace transform; Nanotechnology; Chromatography; Optics; Thermodynamics; Mechanical 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000244875,0.00006051478,0.000108659,0.0001281961,0.00007300598,0.0000319579,0.00007008125,0.00002222893,0.000005882661],"category_scores_gemma":[0.0000465334,0.00005040713,0.00001273349,0.0004342854,0.0001012652,0.0001700485,0.000006512115,0.00007076722,4.503017e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000274364,"about_ca_system_score_gemma":0.00008164903,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001104862,"about_ca_topic_score_gemma":5.388193e-8,"domain_scores_codex":[0.9994729,0.0000110885,0.000206771,0.00007606024,0.0001409703,0.00009222396],"domain_scores_gemma":[0.9996471,0.00002369818,0.00007262446,0.00004508528,0.0001567651,0.00005465734],"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":[0.00001035002,0.00001730267,0.00008992819,0.0000353924,0.000005273591,5.064101e-8,0.0003194277,0.002288361,0.9952157,0.001019833,0.0008991454,0.00009930327],"study_design_scores_gemma":[0.0001147587,0.0002489449,0.00004144262,0.00005560537,0.000008061113,0.00007051038,0.000192343,0.005063001,0.9907344,0.0002690849,0.003145257,0.00005660307],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7562463,0.02480254,0.2185278,0.000009530928,0.00005326452,0.00003996774,5.561384e-7,0.000005586706,0.000314479],"genre_scores_gemma":[0.97163,0.02817722,0.0001455547,0.00001191875,0.00001135411,8.388766e-7,5.568199e-8,0.00000498337,0.00001812222],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2183823,"threshold_uncertainty_score":0.2055543,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01173481482637305,"score_gpt":0.238987693273469,"score_spread":0.2272528784470959,"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."}}