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Record W4224307713 · doi:10.3390/v14050852

Infection with IBV DMV/1639 at a Young Age Leads to Increased Incidence of Cystic Oviduct Formation Associated with False Layer Syndrome

2022· article· en· W4224307713 on OpenAlexaboutno aff
Adrea Mueller Slay, Monique França, Mark W. Jackwood, Brian J. Jordan

Bibliographic record

VenueViruses · 2022
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Virus Infections Studies
Canadian institutionsnot available
FundersMerck Animal HealthU.S. Poultry and Egg Association
KeywordsOviductCoronavirusBiologyInfectious bronchitis virusBronchitisIncidence (geometry)VirologyMedicineImmunologyPhysiologyDiseaseInternal medicineVirusCoronavirus disease 2019 (COVID-19)Infectious disease (medical specialty)Endocrinology

Abstract

fetched live from OpenAlex

Infectious bronchitis virus (IBV) is an avian coronavirus that causes respiratory disease but can affect the reproductive tract of laying-type chickens. If infection occurs in pullets, false layer syndrome, which is characterized by the development of large, fluid-filled cystic oviducts, can occur. Recently, IBV strain DMV/1639 has been detected in parts of Canada and the U.S., where false layer syndrome has occurred, though it is not clear if IBV is the sole cause or if age at infection is an influencing variable. Our study investigates the role and timing of IBV infection on the development of false layer syndrome, using the IBV types DMV/1639 and Massachusetts (Mass). Six groups of 120 SPF chickens were challenged at either three, seven, or fourteen days of age, using either DMV/1639 or Mass IBV. Cystic oviducts were seen in all the challenged groups, and the pullets challenged at 14 days of age had fewer cystic oviducts than pullets challenged at 3 or 7 days of age. The highest percentage of severe histology lesion scores were seen in the 3-day challenge groups. The data collected in this experiment confirm that IBV DMV/1639 causes cystic oviducts and indicate that age at infection plays a role in the pathogenesis of false layer syndrome.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.348
Threshold uncertainty score0.987

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
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 head0.036
GPT teacher head0.242
Teacher spread0.207 · 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.

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

Citations13
Published2022
Admission routes1
Has abstractyes

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