{"id":"W2329479880","doi":"10.1115/imece2003-42724","title":"Numerical Simulation of On-Chip Injection Process With Spatial Gradients of Electrical Conductivity","year":2003,"lang":"en","type":"article","venue":"Fluids Engineering","topic":"Microfluidic and Capillary Electrophoresis Applications","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Microfluidics; Electrokinetic phenomena; Conductivity; Buffer (optical fiber); Voltage; Materials science; Electric field; Chip; Flow (mathematics); Process (computing); Field (mathematics); Mechanics; Computer science; Nanotechnology; Electrical engineering; Engineering; Physics","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":[0.0003953293,0.0005682308,0.0007324817,0.0004674844,0.000714702,0.0007100188,0.0009138646,0.001993165,0.00280101],"category_scores_gemma":[0.001349975,0.0003563671,0.0007045466,0.0005245478,0.0006701975,0.0005495122,0.0004478167,0.0006835343,0.0002099171],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009386681,"about_ca_system_score_gemma":0.00124604,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01574117,"about_ca_topic_score_gemma":0.007135707,"domain_scores_codex":[0.9998056,0.0000431787,0.00001051737,0.0000297005,0.00006154795,0.00004952611],"domain_scores_gemma":[0.999273,0.0004138252,0.00007678228,0.00003894579,0.0001483945,0.00004892215],"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":[0.00003332984,0.00003263522,0.0005902247,0.00003830516,0.00000942696,0.00007873821,0.00003252293,0.9936998,0.001788165,0.002146341,0.0002101164,0.001340388],"study_design_scores_gemma":[0.000005455256,0.000007081702,0.0000688357,0.000001664149,0.000001741404,0.000003834484,0.000004299327,0.9993764,0.0002832407,0.0001445937,0.0001010251,0.000001901925],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7147251,0.001055222,0.2365993,0.001367537,0.0003409424,0.0002650717,0.001260298,0.001289979,0.04309655],"genre_scores_gemma":[0.9578274,0.0003064109,0.03515686,0.00009557304,0.00001912985,0.0002216715,0.0003131461,0.00006034883,0.005999443],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01574117,"threshold_uncertainty_score":0.03129911,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006499969019617785,"score_gpt":0.2066754091611709,"score_spread":0.2001754401415531,"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."}}