{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001194646,0.00009463031,0.0000983728,0.00007518883,0.0001342587,0.00002181784,0.0001605745,0.00003691961,0.000008149156],"category_scores_gemma":[0.0001622379,0.0001068721,0.00002612976,0.0002396326,0.000006495827,0.00001948612,0.00003954552,0.0001474933,0.000007565707],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007866276,"about_ca_system_score_gemma":0.00001678811,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002685962,"about_ca_topic_score_gemma":0.000005173407,"domain_scores_codex":[0.9993897,0.000006897793,0.0001100433,0.0001620252,0.0000964455,0.0002348972],"domain_scores_gemma":[0.9996591,0.0000810013,0.00002147634,0.0001931955,0.0000172294,0.00002803329],"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":[0.00001579674,0.00006230624,0.0001369294,0.00008967068,0.0000199415,0.00000387009,0.0001907158,0.009137787,0.8158424,0.005812005,0.01866701,0.1500215],"study_design_scores_gemma":[0.0001810456,0.0001537267,0.00006264408,0.00001473761,0.00001344486,0.000003362269,0.00008035256,0.001902515,0.7078636,0.002738584,0.2867883,0.0001976667],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5223455,0.004204964,0.4677618,0.0007544673,0.0001697299,0.0009523336,0.0001951072,0.00244294,0.001173099],"genre_scores_gemma":[0.9915563,0.00004774358,0.006783498,0.0005048807,0.00002945956,0.0009027486,0.00005899549,0.00004462857,0.00007174695],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4692107,"threshold_uncertainty_score":0.4358116,"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."}}