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Record W35103420

Comparison of commercial enzyme-linked immunosorbent assays and agar gel immunodiffusion tests for the serodiagnosis of equine infectious anemia.

2004· article· en· W35103420 on OpenAlexaffabout
Julie Paré, Carole Simard

Bibliographic record

VenuePubMed · 2004
Typearticle
Languageen
FieldImmunology and Microbiology
TopicMicrobial infections and disease research
Canadian institutionsCanadian Food Inspection Agency
Fundersnot available
KeywordsOuchterlony double immunodiffusionEquine infectious anemiaAntibodyVirologyImmunodiffusionSerologyBiologyImmunologyVirus
DOInot available

Abstract

fetched live from OpenAlex

The purpose of this study was to estimate the performance characteristics (accuracy, detection limit, and precision) of commercially available enzyme-linked immunosorbent assay (ELISA) and agar gel immunodiffusion (AGID) kits in comparison with a reference AGID kit for the detection of equine infectious anemia (EIA) antibodies in horses for regulatory use in Canada. A total of 285 positive and 315 negative samples by the reference AGID were tested blindly on 2 other AGID and 4 ELISA kits. Commercially available AGID kits for the serodiagnosis of EIA were found equivalent. The 3 ELISAs directed against antibodies to the p26 core protein also performed relatively well in comparison with the reference AGID, with excellent relative accuracy and acceptable precision. The single ELISA directed against antibodies to the gp45 trans-membrane viral protein yielded a lower relative sensitivity. The performance characteristics of the ELISAs directed against antibodies to p26 are, therefore, adequate to support the implementation of ELISA for regulatory purposes in Canada.

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)0.010
metaresearch head score (Gemma)0.028
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.053

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.028
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
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 head0.049
GPT teacher head0.320
Teacher spread0.271 · 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

Citations29
Published2004
Admission routes2
Has abstractyes

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