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Record W2224222815 · doi:10.51791/njap.v31i2.1820

Incidence of trypanosomosis in a Muturu herd at Nsukka, South-Eastern Nigeria

2021· article· en· W2224222815 on OpenAlexaboutno aff
B.M. Anene, J. I. Eze, T. O. Nnaji, K. O. Anya, S. O. Udegbunam, A. G. Ezekwe

Bibliographic record

VenueNigerian Journal of Animal Production · 2021
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicVector-Borne Animal Diseases
Canadian institutionsnot available
Fundersnot available
KeywordsEpizootiologyHerdTrypanosoma vivaxDry seasonIncidence (geometry)Veterinary medicineWet seasonQuarter (Canadian coin)BiologyEast Coast feverTrypanosomiasisAnimal scienceGeographyEcologyMedicineImmunology

Abstract

fetched live from OpenAlex

A herd of 38 Muturu cattle under semi-intensive system of management at the University of Nigeria, Nsukka Agricultural Farm, southeastern, Nigeria, was examined for the presence of trypanosome infection over a one year period (April, 1998 - March, 1999). The aim was to assess the incidence of trypanosoniosis and factors that may affect its occurrence variation. Infection was widespread in the herd (67.9%) during the period. Out of the factors (season, sex and age) only season showed a significant effect on the occurrence of trypanosomosis. The incidence was highest in the third quarter of the year corresponding 10 the late rainy season period, followed by the fourth quarter (early dry season, and was least in the first quarter (late dry season). This seasonal incidence varied between 2.6% (CI, 0.3 - 9.196) to 20.396 (CI,12.0-30.8%) 411 the infections were due to Trypanosoma vivax and the principal tsetse vector was Glossina tachinoides. Parasitaemic animals were able to control anaemia as their PCPs vere similar to those of uninfected animals (P>0.05). The importance of these findings in relation to the general epizootiology of trypanosomosis and animal production in the area is discussed.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.711
Threshold uncertainty score0.658

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.020
GPT teacher head0.229
Teacher spread0.209 · 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

Citations0
Published2021
Admission routes1
Has abstractyes

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