{"id":"W2001244621","doi":"10.1149/1.3571976","title":"Microfluidics for Detection of Myoglobin in Blood Samples","year":2011,"lang":"en","type":"article","venue":"ECS Transactions","topic":"Microfluidic and Capillary Electrophoresis Applications","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Alberta Innovates - Technology Futures; CMC Microsystems","keywords":"Myoglobin; Dielectrophoresis; Microfluidics; Immunoassay; Nanotechnology; Materials science; Chromatography; Chemistry; Biology; Biochemistry; Antibody; Immunology","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":[0.0007517518,0.0003480084,0.0002930575,0.0004775775,0.0002688376,0.0004260982,0.0003449458,0.0004210189,0.0007407791],"category_scores_gemma":[0.0007614042,0.0001940512,0.0002238879,0.0001944247,0.0003060472,0.0003305946,0.0002927467,0.0003490484,0.0002655281],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003847026,"about_ca_system_score_gemma":0.0003788488,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003413605,"about_ca_topic_score_gemma":0.000514415,"domain_scores_codex":[0.9996512,0.00008130042,0.00002585671,0.00007626689,0.0001261963,0.00003913543],"domain_scores_gemma":[0.9997908,0.0001069728,0.00003254505,0.00001281796,0.00003730832,0.0000195814],"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":[0.00006067249,0.00003032544,0.0004369,0.0001682615,0.00001352078,0.00009302559,0.00005785247,0.0002479498,0.9845508,0.001140578,0.0003342908,0.01286579],"study_design_scores_gemma":[0.00002674456,0.0003154867,0.002009802,0.00004263208,0.00003224966,0.0004341908,0.00003745075,0.006834407,0.977232,0.0005734548,0.01243535,0.00002626629],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7298735,0.05641429,0.2019743,0.002907435,0.001523279,0.0003877101,0.000635265,0.0008225568,0.005461717],"genre_scores_gemma":[0.8788221,0.01169822,0.1046255,0.0007182212,0.0002872941,0.0002103256,0.0001940045,0.00002047831,0.003423863],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0007517518,"threshold_uncertainty_score":0.003975689,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01649117522515015,"score_gpt":0.1955776629331982,"score_spread":0.1790864877080481,"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."}}