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Record W2735921096 · doi:10.1089/vim.2017.0050

Hatchery Vaccination Against Poultry Viral Diseases: Potential Mechanisms and Limitations

2017· review· en· W2735921096 on OpenAlexaff
Mohamed Sarjoon Abdul-Cader, Victor Palomino-Tapia, Aruna Amarasinghe, Hanaa Ahmed-Hassan, Upasama De Silva Senapathi, Mohamed Faizal Abdul-Careem

Bibliographic record

VenueViral Immunology · 2017
Typereview
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Virus Infections Studies
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsVaccinationHatcheryIn ovoImmune systemBiologyImmunizationVirologyImmunityImmunologyMedicineEmbryoFish <Actinopterygii>Fishery

Abstract

fetched live from OpenAlex

Commercial broiler and layer chickens are heavily vaccinated against economically important viral diseases with a view of preventing morbidity, mortality, and production impacts encountered during short production cycles. Hatchery vaccination is performed through in ovo embryo vaccination prehatch or spray and subcutaneous vaccinations performed at the day of hatch before the day-old chickens are being placed in barns with potentially contaminated environments. Commercially, multiple vaccines (e.g., live, live attenuated, and viral vectored vaccines) are available to administer through these routes within a short period (embryo day 18 prehatch to day 1 posthatch). Although the ability to mount immune response, especially the adaptive immune response, is not optimal around the hatch, it is possible that the efficacy of these vaccines depends partly on innate host responses elicited in response to replicating vaccine viruses. This review focuses on the current knowledge of hatchery vaccination in poultry and potential mechanisms of hatchery vaccine-mediated protective responses and limitations.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.081
GPT teacher head0.306
Teacher spread0.225 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations55
Published2017
Admission routes1
Has abstractyes

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