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Record W2110426497 · doi:10.1017/s1466252308001606

Veterinary vaccines: alternatives to antibiotics?

2008· review· en· W2110426497 on OpenAlexaff
Andrew Potter, Volker Gerdts, Sylvia van Drunen Littel‐van den Hurk

Bibliographic record

VenueAnimal Health Research Reviews · 2008
Typereview
Languageen
FieldImmunology and Microbiology
TopicMicrobial infections and disease research
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsVaccinationDiseaseMedicineDisease controlInfectious disease (medical specialty)AntibioticsIntensive care medicineDisease preventionImmunologyVirologyBiologyMicrobiologyPathology

Abstract

fetched live from OpenAlex

The prevention of infectious diseases of animals by vaccination has been routinely practiced for decades and has proved to be one of the most cost-effective methods of disease control. However, since the pioneering work of Pasteur in the 1880s, the composition of veterinary vaccines has changed very little from a conceptual perspective and this has, in turn, limited their application in areas such as the control of chronic infectious diseases. New technologies in the areas of vaccine formulation and delivery as well as our increased knowledge of disease pathogenesis and the host responses associated with protection from disease offer promising alternatives for vaccine formulation as well as targets for the prevention of bacterial disease. These new vaccines have the potential to lessen our reliance on antibiotics for disease control, but will only reach their full potential when used in combination with other intervention strategies.

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 score0.005
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0020.004
Open science0.0010.001
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0050.005

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 head0.581
GPT teacher head0.587
Teacher spread0.006 · 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

Citations38
Published2008
Admission routes1
Has abstractyes

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