Association between risk assessment scores and lactating cow Mycobacterium avium subsp paratuberculosis ELISA results on Ontario dairy farms
Bibliographic record
Abstract
Johne's disease (JD) is a chronic, gastrointestinal disease of ruminants, including cattle, caused by Mycobacterium avium subsp paratuberculosis (MAP). After calves become infected by means of ingestion of MAP in feces, colostrum or milk, it usually takes years before signs of JD can be detected. Currently, there is no treatment for JD. Disease control strategies focus on farm management practices to prevent the disease from spreading. Subclinical and clinical JD significantly impairs the production and reduces the slaughter value of affected dairy cattle. Of great concern is the suspected association between JD in cattle and Crohn's disease in humans; however, a definite link between those two diseases has not yet been established. To control JD, the Ontario dairy industry launched the Ontario Johne's Education and Management Assistance Program (OJEMAP) in January 2010. The OJEMAP is based on a veterinary administered on-farm risk assessment and management plan (RAMP), where a high risk score indicates a high risk for MAP transmission. Farmers can test lactating cows for antibodies against MAP by use of an ELISA performed on milk or serum. The RAMP focuses on management strategies for biosecurity, calving area, calf and heifer rearing, lactating and dry-cow hygiene, and general manure handling. As of April 2013, half of all Ontario dairy farms have voluntarily participated in this program; however, an evaluation of the use of the RAMP and its association with Johne's disease in this broader Ontario program has not been conducted. The objective of this cross-sectional study was to determine relationships among RAMP scores, ELISA results, and the recommendations made by the veterinarians administering the RAMP.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".