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Record W2106478036 · doi:10.1637/10206-041512-reg.1

Avian Influenza in North America, 2009–2011

2012· article· en· W2106478036 on OpenAlexaffabout
John Pasick, Janice C. Pedersen, Mario Solis Hernandez

Bibliographic record

VenueAvian Diseases · 2012
Typearticle
Languageen
FieldMedicine
TopicInfluenza Virus Research Studies
Canadian institutionsCanadian Food Inspection Agency
Fundersnot available
KeywordsOutbreakInfluenza A virus subtype H5N1FlockHighly pathogenicBiosecurityHuman mortality from H5N1Avian influenza virusBiologyPandemicVeterinary medicineVirologyVirusCoronavirus disease 2019 (COVID-19)MedicineInfectious disease (medical specialty)DiseaseEcology

Abstract

fetched live from OpenAlex

All reports of avian influenza virus infections in poultry and isolations from wild bird species in Canada, the United States, and Mexico between 2009 and 2011 involved low pathogenic avian influenza. All three countries reported outbreaks of low pathogenic notifiable avian influenza in poultry during this period. The reports involved outbreaks of H5N2 among commercial turkeys in Canada in 2009 and 2010; outbreaks of H5N3 in turkeys in 2009, H5N2 in chickens in 2010, H7N3 in turkeys in 2011, and H7N9 in chickens, turkeys, geese, and guinea fowl in 2011 in the United States; and multiple outbreaks of H5N2 in chickens in Mexico in 2009, 2010, and 2011. Outbreaks of pandemic H1N1 infections in turkey breeder flocks were reported in Canada in 2009 and in the United States in 2010. Active surveillance of live bird markets in the United States led to the detection of H2, H3, H4, H5, H6, and H10 subtypes. Despite the fact that wild bird surveillance programs underwent contraction during this period in both Canada and the United States, H5 and H7 subtypes were still detected.

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)0.001
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 score0.694
Threshold uncertainty score0.608

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.057
GPT teacher head0.356
Teacher spread0.299 · 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

Citations42
Published2012
Admission routes2
Has abstractyes

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