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Record W2610831850 · doi:10.5210/ojphi.v7i1.5951

Community Perceptions on Integrating Animal Vaccination and Health Education by Veterinary and Public Health Workers in the Prevention of Brucellosis among Pastoral Communities of South Western Uganda

2015· article· en· W2610831850 on OpenAlexfundno aff
Catherine Kansiime, Lynn Atuyambe, Victor Guma, Anthony Mugisha, Samuel Mugisha, Benon Asiimwe, Innocent B. Rwego, Elizeus Rutebemberwa

Bibliographic record

VenueOnline Journal of Public Health Informatics · 2015
Typearticle
Languageen
FieldVeterinary
TopicBrucella: diagnosis, epidemiology, treatment
Canadian institutionsnot available
FundersInternational Development Research Centre
KeywordsBrucellosisVaccinationPublic healthGovernment (linguistics)MedicineVeterinary public healthVeterinary medicineOne HealthAnimal healthEnvironmental healthPublic relationsNursingPolitical scienceImmunology

Abstract

fetched live from OpenAlex

Integration of animal vaccination against and health education on brucellosis (the activity level) by veterinary and public health workers (the actors‰Ûª level), how to conduct the integration process, and challenges likely to be faced was conducted in pastoral communities. It was noted that integration of animal vaccination and health education would be feasible if government and other stakeholders were involved in facilitation of the programs. Key areas of improvement mentioned included; improving human resources, facilitating the necessary activities such as sensitization of the communities about the brucellosis, and providing the vaccines and diagnostic kits, collaboration with all stakeholders.

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)0.007
metaresearch head score (Gemma)0.011
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.019
Threshold uncertainty score0.039

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.011
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.003
Scholarly communication0.0030.001
Open science0.0010.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.348
GPT teacher head0.456
Teacher spread0.108 · 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

Citations4
Published2015
Admission routes1
Has abstractyes

Explore more

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