{"id":"W4221041769","doi":"10.1039/d1lc01068a","title":"Portable sample processing for molecular assays: application to Zika virus diagnostics","year":2022,"lang":"en","type":"article","venue":"Lab on a Chip","topic":"Electrowetting and Microfluidic Technologies","field":"Engineering","cited_by":41,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Canadian Institutes of Health Research; University of Toronto; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs; International Development Research Centre","keywords":"Zika virus; Microfluidics; Sample (material); Digital polymerase chain reaction; Molecular diagnostics; Virology; Computer science; Computational biology; Engineering; Computer hardware; Virus; Biology; Nanotechnology; Chromatography; Materials science; Chemistry; Bioinformatics; Polymerase chain reaction","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":[0.001113355,0.001272272,0.0006135833,0.0007354187,0.0004447821,0.001056341,0.001266392,0.001221026,0.007837647],"category_scores_gemma":[0.001555887,0.0006775351,0.0007320083,0.0005001468,0.0006645217,0.0005471154,0.0006545178,0.001410682,0.00341674],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003873484,"about_ca_system_score_gemma":0.0007840273,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006820279,"about_ca_topic_score_gemma":0.001335034,"domain_scores_codex":[0.9990231,0.0001467876,0.00005235616,0.0003397956,0.0003561241,0.00008180963],"domain_scores_gemma":[0.9993431,0.0002708352,0.00008553353,0.000100769,0.0001465477,0.00005318282],"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":[0.0001019919,0.00008820583,0.0003913835,0.0002099463,0.00002209811,0.00007516521,0.00005354251,0.0002125032,0.9789697,0.0002590801,0.001192856,0.01842356],"study_design_scores_gemma":[0.00003809178,0.0003614966,0.002307516,0.00004060293,0.00004810809,0.0003198951,0.00003923159,0.003018938,0.9799294,0.0002957793,0.01356253,0.00003842093],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1269232,0.003773753,0.841997,0.001418081,0.001618717,0.002566599,0.004002776,0.008536128,0.009163711],"genre_scores_gemma":[0.3132931,0.00390742,0.6509176,0.001680604,0.0005452272,0.002682233,0.00396279,0.0008815194,0.02212952],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007837647,"threshold_uncertainty_score":0.02621955,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006977636648789688,"score_gpt":0.220995579935318,"score_spread":0.2140179432865283,"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."}}