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Vaccination of Animals

2018· other· en· W4245755064 on OpenAlexaff
Lorne A. Babiuk, Gerald L. Stokka, James Gaspers

Bibliographic record

VenueEncyclopedia of Life Sciences · 2018
Typeother
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Disease Management and Epidemiology
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsVaccinationImmune systemDiseaseImmunologyInfectious disease (medical specialty)ImmunityMedicine

Abstract

fetched live from OpenAlex

Abstract The practice of vaccination to elicit an immune response has been utilised to reduce the risk of infectious disease for hundreds of years. Regarding the health of livestock, vaccination remains one of the most, if not the most, important management tools for the prevention of infectious diseases. The goal of any vaccine and vaccination protocol is to reduce the risks associated with the development of clinical disease. Various approaches can be employed to improve animal health through vaccination. Owing to the unique management situation faced by different species, each has its own difficulties associated with vaccine delivery and eliciting the proper long‐lived immunologic responses. Understanding these difficulties with vaccine delivery, the pathogens themselves and the specific species immune response to vaccine antigens is critical to further reduce the risks of clinical disease. Key Concepts Infectious diseases continue to persist in animal populations and it is critical to understand each individual species from a management standpoint as well as the pathogenesis of the infectious agent in order to illicit the specific immune response required to deliver life‐long protection from clinical disease. Understanding the passive transfer of immunity from mother to offspring as well its effect on the neonate's ability to produce a proper immune response to vaccine antigens is required. Anticipating stressful events in an animal's life and applying vaccination protocols before those events take place so that the animal's immune system is effectively able to recognise and combat the antigen(s) is critical to the success of the vaccine and the animal. Matching economic viability and vaccination principles with vaccination protocols is required to achieve biological control of pathogens. Understanding various routes of vaccine administration and the specific immune response they illicit is necessary for the success of a vaccine and vaccination protocol. Understanding the dynamics of pathogen transmission and the concept of herd immunity. Cooperation among research scientists, veterinarians, owners of the animals and government agencies is critical for the widespread eradication of specific diseases.

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: Other · Consensus signal: Other
Teacher disagreement score0.015
Threshold uncertainty score0.050

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0150.006

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 head0.030
GPT teacher head0.269
Teacher spread0.239 · 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
GenreOther

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
Published2018
Admission routes1
Has abstractyes

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