Association between caudal fold tuberculin test responses and results of an ELISA for Mycobacterium avium subsp paratuberculosis and mycobacterial culture of feces in tuberculosis-free dairy herds
Bibliographic record
Abstract
OBJECTIVE--To evaluate associations between Mycobacterium avium subsp paratuberculosis (MAP) and caudal fold tuberculin (CFT) test results in cattle. DESIGN--Longitudinal and cross-sectional evaluations. ANIMALS--1 California (approx 3,600 cows) and 3 Colorado (approx 640, 1,190, and 1,480 cows) dairy herds considered free of Mycobacterium bovis infection. PROCEDURES--In the California herd, the association between CFT response and MAP status was determined with ELISA and mycobacterial culture of feces within 1 year before and after CFT testing. The association between CFT and MAP status in all herds was modeled with mixed-effects logistic regression. RESULTS--In the California herd, significantly higher odds of being classified as suspect by CFT were found for cows with results of MAP ELISA negative before and positive after CFT testing (OR, 5.6) and cows positive before and after CFT testing (OR, 8.1). Higher odds were found for cows positive for mycobacterial culture of feces before and negative for culture after CFT testing (OR, 4.6) and cows negative for mycobacterial culture of feces before and positive for culture after CFT testing (OR, 13.2). All herds had higher odds of being classified as suspect by CFT testing for cows with positive results for ELISA (OR, 2.9) or mycobacterial culture of feces (OR, 5.0), compared with cows with negative results of the same tests. CONCLUSIONS AND CLINICAL RELEVANCE--A strong association was found between positive MAP test results and being classified as a suspect by CFT testing. Within-herd MAP prevalence may affect specificity of CFT testing for tuberculosis in cattle.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".