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Record W1454533746 · doi:10.3133/fs20153060

USGS highly pathogenic avian influenza research strategy

2015· article· en· W1454533746 on OpenAlexaboutno aff
M. Camille Harris, A. Keith Miles, John M. Pearce, Diann J. Prosser, Jonathan M. Sleeman, Mary E. Whalen

Bibliographic record

VenueFact sheet · 2015
Typearticle
Languageen
FieldMedicine
TopicInfluenza Virus Research Studies
Canadian institutionsnot available
Fundersnot available
KeywordsInfluenza A virus subtype H5N1Highly pathogenicOutbreakPoultry farmingPandemicWildlifeBird migrationBiologyAvian influenza virusGeographyVirusVirologyEcologyCoronavirus disease 2019 (COVID-19)DiseaseInfectious disease (medical specialty)Medicine

Abstract

fetched live from OpenAlex

First posted September 9, 2015 For additional information, contact: Anne Kinsinger USGS Associate Director for Ecosystems 703-648-4050akinsinger@usgs.gov M. Camille Harris USGS Wildlife Disease Coordinator 703-648-4019mcharris@usgs.gov Avian influenza viruses are naturally occurring in wild birds such as ducks, geese, swans, and gulls. These viruses generally do not cause illness in wild birds, however, when spread to poultry they can be highly pathogenic and cause illness and death in backyard and commercial farms. Outbreaks may cause devastating agricultural economic losses and some viral strains have the potential to infect people directly. Furthermore, the combination of avian influenza viruses with mammalian viruses can result in strains with the ability to transmit from person to person, possibly leading to viruses with pandemic potential. All known pandemic influenza viruses have had some genetic material of avian origin. Since 1996, a strain of highly pathogenic avian influenza (HPAI) virus, H5N1, has caused infection in wild birds, losses to poultry farms in Eurasia and North Africa, and led to the deaths of several hundred people. Spread of the H5N1 virus and other influenza strains from China was likely facilitated by migratory birds. In December 2014, HPAI was detected in poultry in Canada and migratory birds in the United States. Since then, HPAI viruses have spread to large parts of the United States and will likely continue to spread through migratory bird flyways and other mechanisms throughout North America. In the United States, HPAI viruses have severely affected the poultry industry with millions of domestic birds dead or culled. These strains of HPAI are not known to cause disease in humans; however, the Centers for Disease Control and Prevention (CDC) advise caution when in close contact with infected birds. Experts agree that HPAI strains currently circulating in wild birds of North America will likely persist for the next few years. This unprecedented situation presents risks to the poultry industry, natural resource management, and potentially human health. Scientific knowledge and decision support tools are urgently needed to understand factors affecting the persistence of HPAI in wild birds, to forecast future spread of HPAI by wild birds, and to detect novel strains of HPAI that may emerge.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.188
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.004

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.356
GPT teacher head0.477
Teacher spread0.121 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2015
Admission routes1
Has abstractyes

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