{"id":"W4362135347","doi":"10.1101/2023.03.30.534984","title":"Targeted genomic sequencing of avian influenza viruses in wetlands sediment from wild bird habitats","year":2023,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Influenza Virus Research Studies","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Provincial Health Services Authority; University of British Columbia; Ministry of Agriculture, Food and Rural Affairs; Government of British Columbia; Canadian Wildlife Federation; Ministry of Health","funders":"British Columbia Centre for Disease Control","keywords":"Biology; Genome; Influenza A virus subtype H5N1; Influenza A virus; Outbreak; Neuraminidase; Metagenomics; Shotgun sequencing; Virology; Pandemic; Subtyping; Zoology; Virus; Genetics; Coronavirus disease 2019 (COVID-19); Gene; Infectious disease (medical specialty); Disease","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.0001536293,0.0004103104,0.0002467682,0.0009909681,0.0005696828,0.0006216143,0.0002556208,0.000321718,0.000563001],"category_scores_gemma":[0.0003994466,0.000161831,0.0002740682,0.0009030057,0.0002524097,0.00007037772,0.0003170167,0.0002135088,0.000475082],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004850166,"about_ca_system_score_gemma":0.0008514694,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.08194543,"about_ca_topic_score_gemma":0.1733745,"domain_scores_codex":[0.9997974,0.00001398311,0.00001118372,0.00005879814,0.00007517076,0.00004344663],"domain_scores_gemma":[0.9997768,0.00002804134,0.00004472732,0.00001457498,0.00009729679,0.00003861417],"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":[0.0002200353,0.00007555482,0.126927,0.000154823,0.00005944895,0.000615853,0.0008065743,0.0007109818,0.8488299,0.00007773092,0.0007287073,0.0207934],"study_design_scores_gemma":[0.00002330927,0.0003167438,0.877614,0.00004179128,0.0001130835,0.001291571,0.00177657,0.002667822,0.1067302,0.0000898664,0.009313315,0.0000217771],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.984239,0.0004700339,0.006459559,0.00005881341,0.00001534945,0.00008693484,0.006842489,0.0001409553,0.001686799],"genre_scores_gemma":[0.9602324,0.0005892152,0.02018484,0.0001855217,0.00001399928,0.00006334823,0.01650615,0.00007931037,0.002145245],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08194543,"threshold_uncertainty_score":0.1629369,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0786681864302704,"score_gpt":0.3153229348191372,"score_spread":0.2366547483888668,"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."}}