{"id":"W2969877110","doi":"10.1016/j.snb.2019.127017","title":"Fully-functional semi-automated microfluidic immunoassay platform for quantitation of multiple samples","year":2019,"lang":"en","type":"article","venue":"Sensors and Actuators B Chemical","topic":"Microfluidic and Capillary Electrophoresis Applications","field":"Engineering","cited_by":29,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Manitoba","funders":"National Key Research and Development Program of China; National Natural Science Foundation of China","keywords":"Microfluidics; Immunoassay; Detection limit; Chromatography; Microfluidic chip; Biomedical engineering; Computer science; Biomarker; Lab-on-a-chip; Nanotechnology; Materials science; Chemistry; Biology; Immunology; Medicine; Antibody; Biochemistry","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":[0.00006964766,0.0001484213,0.0002125739,0.00006006737,0.00004197587,0.0000137642,0.00006435045,0.00012643,0.0000724251],"category_scores_gemma":[0.00002803972,0.0001415826,0.00007817385,0.000109696,0.00004641448,0.00006261198,0.00001450384,0.00008455277,0.00001724299],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003568139,"about_ca_system_score_gemma":0.00001813519,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009797084,"about_ca_topic_score_gemma":2.51771e-7,"domain_scores_codex":[0.9992514,0.000004812917,0.0002588708,0.0001800813,0.0001009688,0.0002038598],"domain_scores_gemma":[0.9995122,0.0001860007,0.00004305879,0.0001479784,0.00005681063,0.00005395117],"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":[0.00004940272,0.00001911007,0.0005720945,0.0001031577,0.00005083518,8.332297e-8,0.00008021155,0.00001482923,0.9811137,0.0008480433,0.01678246,0.0003660961],"study_design_scores_gemma":[0.0006149322,0.00004016911,0.0007282487,0.00002087565,0.00002350512,0.000009466307,0.0001411981,0.01030944,0.9692865,0.0002680136,0.01836602,0.0001916362],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9914314,0.005520417,0.002328505,0.00002160466,0.00008109939,0.0002751177,0.00007382274,0.0001991341,0.00006886016],"genre_scores_gemma":[0.9952921,0.004097529,0.0002435254,0.00001681028,0.00004300107,0.00002473576,0.0002153612,0.00003060429,0.0000363627],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01182719,"threshold_uncertainty_score":0.577357,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01000366162055234,"score_gpt":0.2073663794458407,"score_spread":0.1973627178252884,"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."}}