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Record W1988668970 · doi:10.7589/0090-3558-46.3.981

Canada Geese and the Epidemiology of Avian Influenza Viruses

2010· article· en· W1988668970 on OpenAlexaboutno aff
Mark T. Harris, Justin D. Brown, Virginia H. Goekjian, M. Page Luttrell, Rebecca L. Poulson, Benjamin R. Wilcox, David E. Swayne, David E. Stallknecht

Bibliographic record

VenueJournal of Wildlife Diseases · 2010
Typearticle
Languageen
FieldMedicine
TopicInfluenza Virus Research Studies
Canadian institutionsnot available
FundersNational Institutes of Health
KeywordsGooseBiologyBrantaFecesAnseriformesWaterfowlVirusInfluenza A virus subtype H5N1ZoologyOutbreakAnatidaeVirologyInfluenza A virusVeterinary medicineEcologyHabitat

Abstract

fetched live from OpenAlex

Canada geese (Branta canadensis) are numerous, highly visible, and widely distributed in both migratory and resident populations in North America; as a member of the order Anseriformes, they are often suggested as a potential reservoir and source for avian influenza (AI) viruses. To further examine the role of Canada Geese in the ecology of AI, we re-evaluated existing literature related to AI virus in this species and tested breeding populations of Canada Geese from three states (Georgia, West Virginia, and Minnesota, USA) by virus isolation and serology. The ability of AI virus to persist in goose feces under experimental conditions also was evaluated as an additional measure of the potential for this species to serve as an AI virus reservoir. Virus was not isolated from 1,668 cloacal swabs and type-specific antibody prevalence was low (4/335, 1.2%). Finally, under experimental conditions, AI virus persistence in goose feces and in water contaminated with goose feces was limited as compared to published estimates from duck feces and water. Our results are consistent with historic reports of a low prevalence of AI virus infection in this species, and we suggest that Canada Geese play a minor, if any, role as a reservoir for low pathogenic AI viruses that naturally circulate in wild bird populations.

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)0.001
metaresearch head score (Gemma)0.016
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.037
Threshold uncertainty score0.993

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.016
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.061
GPT teacher head0.380
Teacher spread0.319 · 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 designObservational
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

Citations42
Published2010
Admission routes1
Has abstractyes

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