{"id":"W2993893494","doi":"10.7589/2019-05-135","title":"TARGETED RESEQUENCING OF WETLAND SEDIMENT AS A TOOL FOR AVIAN INFLUENZA VIRUS SURVEILLANCE","year":2019,"lang":"en","type":"article","venue":"Journal of Wildlife Diseases","topic":"Influenza Virus Research Studies","field":"Medicine","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"BC Centre for Disease Control; Government of British Columbia; University of British Columbia","funders":"Simon Fraser University; Genome British Columbia; Canadian Food Inspection Agency; Compute Canada; Genome Canada","keywords":"Waterfowl; Biology; Outbreak; Virus; Hemagglutinin (influenza); Neuraminidase; Feces; Virology; Influenza A virus subtype H5N1; Influenza A virus; Wetland; Veterinary medicine; Ecology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006403564,0.0001912952,0.0007442549,0.0002872345,0.00007389938,0.00002378706,0.0001890913,0.00006479779,0.0001507708],"category_scores_gemma":[0.003053033,0.0001415512,0.0003722752,0.0002208717,0.0001136947,0.0002180308,0.00007014232,0.0002228022,0.00002713701],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001860314,"about_ca_system_score_gemma":0.0007461872,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006794116,"about_ca_topic_score_gemma":0.000005273376,"domain_scores_codex":[0.9975489,0.00009547859,0.000825891,0.000182175,0.0009629509,0.0003846198],"domain_scores_gemma":[0.9972265,0.0004835317,0.0005626833,0.0003001354,0.001139777,0.0002874012],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.007377645,0.0003470819,0.9334903,0.0007865949,0.0007616146,0.00009328777,0.0003224347,0.0002015512,0.04354167,0.00005357013,0.0123601,0.0006640948],"study_design_scores_gemma":[0.01195014,0.003818927,0.9152874,0.001287071,0.0003316711,0.00009058275,0.0005866452,0.0001207212,0.01370157,0.0003858273,0.0520915,0.0003479344],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9928181,0.005111486,0.00002144551,0.0007244168,0.000206746,0.0007296132,0.0001887291,0.00001471084,0.0001847581],"genre_scores_gemma":[0.9958128,0.0004078923,0.0005437743,0.002564124,0.0004173436,0.00001842263,0.000008891984,0.00003214355,0.0001945501],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0397314,"threshold_uncertainty_score":0.5772291,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03912719469566853,"score_gpt":0.3596991519806697,"score_spread":0.3205719572850012,"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."}}