{"id":"W4409388104","doi":"10.1016/j.tvjl.2025.106356","title":"Visual recombinase aided amplification technology for detecting feline coronavirus","year":2025,"lang":"en","type":"article","venue":"The Veterinary Journal","topic":"Viral gastroenteritis research and epidemiology","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Overseas Expertise Introduction Center for Discipline Innovation of Food Nutrition and Human Health (111 Center)","keywords":"Coronavirus disease 2019 (COVID-19); Coronavirus; Virology; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Recombinase; 2019-20 coronavirus outbreak; Recombinase Polymerase Amplification; Computer science; Biology; Medicine; Genetics; Infectious disease (medical specialty); Pathology; Loop-mediated isothermal amplification; DNA; Recombination","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001152121,0.0008616758,0.0003976386,0.0008055292,0.0002084215,0.0004386038,0.0005741376,0.0009746355,0.0009211212],"category_scores_gemma":[0.0009400783,0.0004576654,0.0005222748,0.0003304021,0.0005046261,0.0004673445,0.0003496268,0.0007618981,0.0006136608],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003712396,"about_ca_system_score_gemma":0.0003046993,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004143519,"about_ca_topic_score_gemma":0.0005229979,"domain_scores_codex":[0.9986669,0.0003697265,0.00006186875,0.000474733,0.0003396602,0.00008710575],"domain_scores_gemma":[0.9995752,0.0001821246,0.0001074502,0.00003766563,0.00007323935,0.00002421589],"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":[0.00001979309,0.00001540765,0.0001693083,0.000069221,0.000004323674,0.00002883355,0.00002730785,0.00005373829,0.9940829,0.00007853183,0.0000328012,0.005417922],"study_design_scores_gemma":[0.00001219595,0.0005355586,0.002310887,0.00001971477,0.00003468846,0.0006433061,0.00002808886,0.002516489,0.9899029,0.0001016316,0.003875182,0.00001938511],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4709995,0.006912604,0.5142398,0.0004113314,0.0001524824,0.0006036747,0.0003971937,0.001554383,0.004729102],"genre_scores_gemma":[0.6543305,0.003005744,0.3354256,0.0003289692,0.000052798,0.0005029613,0.0008006491,0.00008538603,0.005467438],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001152121,"threshold_uncertainty_score":0.006093085,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09173975365949737,"score_gpt":0.4425345819034318,"score_spread":0.3507948282439344,"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."}}