Development of a Lateral Flow Assay for Rapid Detection of Bovine Antibody to<i>Anaplasma marginale</i>
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".