MétaCan
Menu
Back to cohort
Record W2411511565 · doi:10.20506/rst.23.3.1545

Serological diagnosis of bovine brucellosis : a review of test performance and cost comparison

2004· review· fr· W2411511565 on OpenAlexaff
D. Gall, K. Nielsen

Bibliographic record

VenueRevue Scientifique et Technique de l OIE · 2004
Typereview
Languagefr
FieldVeterinary
TopicBrucella: diagnosis, epidemiology, treatment
Canadian institutionsCanadian Food Inspection Agency
Fundersnot available
KeywordsComplement fixation testBovine brucellosisBrucellosisBrucella abortusDirect agglutination testSerologyBrucellaPiMedicineImmunologyChemistryAntibodyBiochemistry

Abstract

fetched live from OpenAlex

The authors reviewed over 50 publications in which the sensitivity and specificity values of assays used for the detection of exposure to Brucella abortus had been examined. The sum of the sensitivity and specificity values for each test was averaged to give a performance index (PI) and allow for a comparison between the different methodologies. A score of 200 was perfect. Based on the PI, the buffered antigen plate agglutination test (BPAT) rated highest (PI = 193.1) among the conventional tests. This indicates better accuracy than the other conventional tests including the Rose Bengal test (PI = 167.6) and the complement fixation test (PI = 172.5). Overall, the primary binding assays, including the fluorescence polarisation assay (PI = 196.4), the indirect enzyme-linked immunosorbent assay (PI = 189.8) and the competitive enzyme-linked immunosorbent assay (PI = 188.2), were more accurate than the conventional tests, except for the BPAT. In addition, a fee comparison suggested that the primary binding tests were price competitive with conventional tests for the diagnosis of brucellosis and, therefore, had a better combined cost/efficiency rating.

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)0.005
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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.011
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.011
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0110.011
Science and technology studies0.0000.001
Scholarly communication0.0020.002
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.130
GPT teacher head0.390
Teacher spread0.260 · 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

Citations204
Published2004
Admission routes1
Has abstractyes

Explore more

Same venueRevue Scientifique et Technique de l OIESame topicBrucella: diagnosis, epidemiology, treatmentFrench-language works237,207