{"id":"W2109133231","doi":"10.1177/104063871002200309","title":"Single-Step Multiplex Conventional and Real-Time Reverse Transcription Polymerase Chain Reaction Assays for Simultaneous Detection and Subtype Differentiation of <i>Influenza A Virus</i> in Swine","year":2010,"lang":"en","type":"article","venue":"Journal of Veterinary Diagnostic Investigation","topic":"Influenza Virus Research Studies","field":"Medicine","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"Cegep de Saint Hyacinthe; Canadian Food Inspection Agency","funders":"Ministère de l'Agriculture, des Pêcheries et de l'Alimentation","keywords":"Reverse transcription polymerase chain reaction; Multiplex; Reverse transcriptase; Virology; Real-time polymerase chain reaction; Polymerase chain reaction; Multiplex polymerase chain reaction; Biology; Virus; Influenza A virus; Molecular biology; Gene; Genetics; Gene expression","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":[0.0007734596,0.0001711839,0.0003773034,0.0004357011,0.00009568401,0.00002119345,0.00003975895,0.0001584535,0.00001048262],"category_scores_gemma":[0.00541884,0.0001624834,0.00008309815,0.0001753938,0.0002106076,0.0003843973,0.00001922984,0.0003084508,9.876895e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001119676,"about_ca_system_score_gemma":0.00008112226,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002391191,"about_ca_topic_score_gemma":0.00008934428,"domain_scores_codex":[0.9983823,0.0001380407,0.0007503899,0.0001925411,0.0003508817,0.0001858126],"domain_scores_gemma":[0.9972169,0.001486597,0.0005667844,0.0001060489,0.0004754657,0.0001482315],"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":[0.002463863,0.0002250809,0.006695936,0.0003445534,0.00005914804,0.00003891579,0.0004398705,0.0000266096,0.9837192,0.00003208978,0.00002386653,0.005930851],"study_design_scores_gemma":[0.01591391,0.01168205,0.4983407,0.001546352,0.0005545898,0.001301942,0.0003415319,0.03020793,0.4377785,0.0008363744,0.00105562,0.0004405546],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9979743,0.000197554,0.0005616801,0.0002886584,0.0002230997,0.0006910178,0.00003591656,0.00001412615,0.00001358648],"genre_scores_gemma":[0.9968041,0.0003355949,0.002454787,0.0001161558,0.0001939424,0.00002894309,0.0000297013,0.00002151563,0.00001525374],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5459408,"threshold_uncertainty_score":0.6625881,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05092327387150399,"score_gpt":0.3163199721456334,"score_spread":0.2653966982741294,"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."}}