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Record W18712347

Serologic detection of antibodies to Brucella spp. using a commercial ELISA in cattle in Grenada, West Indies.

2013· article· en· W18712347 on OpenAlexaboutno aff
Alfred Chikweto, Keshaw Tiwari, Sachin Kumthekar, Diana M. Stone, Bowen Louison, Derek Thomas, Ravindra Sharma, H. Hariharan

Bibliographic record

VenuePubMed · 2013
Typearticle
Languageen
FieldVeterinary
TopicBrucella: diagnosis, epidemiology, treatment
Canadian institutionsnot available
Fundersnot available
KeywordsBrucellosisHerdBrucella abortusSerologyBiologyBrucellaBrucella melitensisVeterinary medicineBrucellaceaeAntibodyBovine brucellosisWest indiesVirologyAnimal scienceImmunologyMedicine
DOInot available

Abstract

fetched live from OpenAlex

Bovine brucellosis, caused mainly by Brucella abortus, a zoonotic bacterium, has been reported from many areas of the world, including Central and South America, and the Caribbean island state of Trinidad and Tobago. Although brucellosis has been eradicated from domestic cattle in Canada it still exists in one or two herds in the United States. Serological tests are important in estimating prevalence of Brucella exposure in order to target eradication programmes. In this study, serum samples from 150 cattle were tested using a commercial competitive enzyme linked immunosorbent assay (SVANOVIR®Brucella-Ab C-ELISA) which detects antibodies to both B. abortus and Brucella melitensis. All cattle tested were greater than 6 months old and were unvaccinated. Sampled cattle were from 35 herds representing animals from all 6 parishes of Grenada. Nine of the 150 animals (6%) were positive for antibodies to B. abortus and/or melitensis by the C-ELISA. Of the 35 herds, 7 (20%) had C-ELISA- positive animals. Three of the 6 parishes contained positive herds. Based on the high sensitivity (98%) and specificity (99.7%) of the C-ELISA, these results strongly indicate the presence of cattle exposed to B. abortus and/or melitensis in Grenada.

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)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.035
Threshold uncertainty score0.988

Codex and Gemma teacher scores by category

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

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 head0.112
GPT teacher head0.319
Teacher spread0.206 · 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

Citations7
Published2013
Admission routes1
Has abstractyes

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