Investigation of the cause of geographic disparities in IDEXX ELISA sensitivity in serum samples from Mycobacterium bovis-infected cattle
Bibliographic record
Abstract
Accurately identifying Mycobacterium bovis-infected cattle is critical for bovine tuberculosis prevention and control. One method for identifying infected cattle is an ELISA developed by IDEXX laboratories, which detects antibodies to two M. bovis proteins, MPB70 and MPB83. The assay's sensitivity varies by geographic region, with sensitivities of 77%, 45%, and 9% in bovine serum samples from the United Kingdom (n = 126), the United States (n = 146), and Mexico (n = 128), respectively. We hypothesized that geographically-biased sequence variation in mpb70 and mpb83, or in the genes that regulate their expression (sigK and rskA), may explain these differing sensitivities. This hypothesis was tested by comparing the sequences of these four genes in 455 M. bovis strains isolated from cattle in the aforementioned countries. For each gene, a single, common sequence was identified in most genomes of the M. bovis strains collected in all three countries. Twelve of the 455 strains were isolated from infected cattle for which the IDEXX ELISA was also performed. Five of the seven ELISA-positive genomes and three of the five ELISA-negative genomes contained the most common sequence of all four genes. Thus, sequence variation in mpb70, mpb83, sigK, and rskA does not explain the geographic disparities in IDEXX ELISA sensitivity.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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 teacher head, 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".