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Record W2063579012 · doi:10.1080/15321810701734693

Development of a Lateral Flow Assay for Rapid Detection of Bovine Antibody to<i>Anaplasma marginale</i>

2007· article· en· W2063579012 on OpenAlexafffundabout
Klaus Nielsen, Yu Wang, L. Kelly, R. Bermudez, T. Renteria, A. Dajer, Elain Gutierrez, Joy Williams, J. Algire, S. Torioni de Eschaide

Bibliographic record

VenueJournal of Immunoassay and Immunochemistry · 2007
Typearticle
Languageen
FieldImmunology and Microbiology
TopicVector-borne infectious diseases
Canadian institutionsCanadian Food Inspection Agency
FundersCanadian Food Inspection Agency
KeywordsAnaplasmosisBiologyVirologyImmunoassayAntibodyAntigenAnaplasmaMonoclonal antibodySeroprevalenceMolecular biologySerologyImmunology

Abstract

fetched live from OpenAlex

A rapid lateral flow assay for detection of bovine antibody to Anaplasma marginale was developed. The assay used a recombinant peptide of major surface protein 5 as the antigen and a monoclonal antibody specific for bovine IgG(1) conjugated with colloidal gold beads for detection. Serum and anticoagulated blood samples were obtained from cattle in an area where anaplasmosis was endemic. The samples were selected based on positive identification of the organism in blood smears. The unclotted blood samples were used for PCR determination of the presence of A. marginale while the sera were tested by a commercial competitive enzyme immunoassay (CELISA) and by the lateral flow assay (LFA). Similar samples, collected at a Canadian sales barn, were tested by the CELISA and LFA and 10% were tested by PCR for the presence of A. marginale nucleic acid. In addition, stored serum samples from a second endemic area were tested by CELISA and LFA. Of the 114 smear positive samples, all were positive by CELISA and LFA. All samples were also positive by PCR. Samples from Canadian sources (n=524) were negative in the CELISA but 11 sera gave false positive reactions in the LFA. All samples tested were PCR negative. Of 113 samples from herds with anaplasmosis, 53 were positive in the CELISA and 50 were LFA positive.

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)0.002
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.028
Threshold uncertainty score0.867

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 head0.007
GPT teacher head0.246
Teacher spread0.239 · 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 designBench or experimental
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

Citations37
Published2007
Admission routes3
Has abstractyes

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