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Record W1752244600

Influenza viruses from wild birds in Newfoundland and Labrador in the context of global influenza dynamics

2010· dissertation· en· W1752244600 on OpenAlexaboutno aff
Michelle Wille

Bibliographic record

VenueMemorial University Research Repository (Memorial University) · 2010
Typedissertation
Languageen
FieldMedicine
TopicInfluenza Virus Research Studies
Canadian institutionsnot available
Fundersnot available
KeywordsWaterfowlAnasContext (archaeology)GeographySubarctic climateInfluenza A virus subtype H5N1BiologyZoologyCharadriiformesEcologyFisheryHabitatVirologyVirusArchaeology
DOInot available

Abstract

fetched live from OpenAlex

The primary hosts for avian influenza A viruses (AIV) are waterfowl and shorebirds, although other groups such as seabirds and gulls also serve as hosts. Newfoundland is an important breeding area for boreal and subarctic birds, and a wintering location for some high-latitude North American, and Eurasian species. I gathered 2873 samples from seabirds, gulls and waterfowl in Newfoundland and Labrador during 2008-2010. The overall detection rate of AIV in these birds was low, but viruses were identified in Common Murre (Uria aalgae), Thick-billed Murre (U. lomvia), American Black Duck (Anas rubrpies), Great Black-backed Gull (Larus marinus), and other unknown gull species. An AIV isolated from a Great Black-backed Gull in 2008 had segments with a mosaic pattern of geographical origins, indicating transatlantic transmission of AIV between Newfoundland and Europe. These findings, as well as analyses of six viruses sequenced from gulls in Alaska and all gull AIV sequences available in public databases, suggest that large gulls may play an important role in AIV dynamics, especially in the context of global movements.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.314
Threshold uncertainty score0.632

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.047
GPT teacher head0.338
Teacher spread0.291 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations0
Published2010
Admission routes1
Has abstractyes

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