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Record W2026393383 · doi:10.1128/cdli.7.5.828-831.2000

Evaluation of Primary Binding Assays for Presumptive Serodiagnosis of Swine Brucellosis in Argentina

2000· article· en· W2026393383 on OpenAlexafffundabout
P. Silva Paulo, Ana M. Vigliocco, R Ramondino, D H Marticorena, E. Bissi, Gabriel Briones, C Gorchs, D. Gall, K. Nielsen

Bibliographic record

VenueClinical and Diagnostic Laboratory Immunology · 2000
Typearticle
Languageen
FieldVeterinary
TopicBrucella: diagnosis, epidemiology, treatment
Canadian institutionsCanadian Food Inspection Agency
FundersCanadian Food Inspection Agency
KeywordsBrucellosisSerologyDirect agglutination testBrucella abortusBrucella suisVeterinary medicineBrucellaceaeHerdBiologyBrucellaVirologyAntibodyMedicineImmunologyBrucella melitensis

Abstract

fetched live from OpenAlex

An indirect enzyme-linked immunosorbent assay (IELISA), a competitive ELISA (CELISA), and a fluorescence polarization assay (FPA) for the presumptive serological diagnosis of swine brucellosis were evaluated using two populations of swine sera: sera from brucellosis-free Canadian herds and sera from Argentina selected based on positive reactions in the buffered antigen plate agglutination test (BPAT) and the 2-mercaptoethanol (2-ME) test. In addition, sera from adult swine from which Brucella suis was isolated at least once for each farm of origin were evaluated. The IELISA, CELISA, and FPA specificity values were 99.9, 99.5, and 98. 3%, respectively, and the IELISA, CELISA, and FPA sensitivity values relative to the BPAT and the 2-ME test were 98.9, 96.6, and 93.8%, respectively. Actual sensitivity was assessed by using 37 sera from individual pigs from which B. suis was cultured, and the values obtained were as follows: BPAT, 86.5%; 2-ME test, 81.1%; IELISA, 86.5%; CELISA, 78.5%; and FPA, 80.0%.

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)0.002
metaresearch head score (Gemma)0.002
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 score0.008
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.162
GPT teacher head0.411
Teacher spread0.249 · 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

Citations38
Published2000
Admission routes3
Has abstractyes

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