{"id":"W2886489997","doi":"10.1111/tbed.12994","title":"Fully automated and integrated multiplex detection of high consequence livestock viral genomes on a microfluidic platform","year":2018,"lang":"en","type":"article","venue":"Transboundary and Emerging Diseases","topic":"Animal Disease Management and Epidemiology","field":"Agricultural and Biological Sciences","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Lethbridge; Canadian Food Inspection Agency","funders":"Safety, Security, and Quality Assurance; Canadian Food Inspection Agency; National Pork Board","keywords":"Multiplex; Vesicular Stomatitis; Virology; Biology; Virus; Vesicular stomatitis virus; Serotype; Multiplex polymerase chain reaction; Computational biology; Polymerase chain reaction; Bioinformatics","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":[0.00008198668,0.0001611503,0.0002159533,0.00002988894,0.0003590034,0.00003515699,0.00008561764,0.00005686384,0.0001351671],"category_scores_gemma":[0.0000325059,0.00007457097,0.00005598659,0.0001467143,0.0005959577,0.0001380144,0.00002531689,0.00005881907,0.000007492697],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000009969082,"about_ca_system_score_gemma":0.000009944713,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007811383,"about_ca_topic_score_gemma":0.0001619692,"domain_scores_codex":[0.9991322,0.0000631438,0.0002106067,0.0002900415,0.00008032333,0.0002236429],"domain_scores_gemma":[0.9996117,0.0001224756,0.00006318872,0.00004053654,0.00004067781,0.0001213831],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.003021756,0.0002820369,0.03894521,0.0001663645,0.0001669017,0.00002999762,0.0003945309,0.000004873461,0.7485002,0.001446299,0.0007169523,0.2063249],"study_design_scores_gemma":[0.0004597463,0.001810386,0.9855074,0.00007733927,0.0001150908,0.000007934004,0.0003866649,0.001467456,0.003120993,0.001554478,0.00521675,0.0002757618],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9963677,0.002661519,0.00003133656,0.000298885,0.00006599533,0.0001762389,0.0001447792,0.0001898114,0.00006374317],"genre_scores_gemma":[0.9987365,0.0007810445,0.00002618092,0.0002519264,0.00008134,0.00001112161,0.00007753728,0.000001585299,0.00003277452],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9465622,"threshold_uncertainty_score":0.3040916,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01895087705791549,"score_gpt":0.237253984429891,"score_spread":0.2183031073719756,"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."}}