Risk factors for herds to test positive for Mycobacterium avium ssp. paratuberculosis-antibodies with a commercial milk enzyme-linked immunosorbent assay (ELISA) in Ontario and western Canada.
Bibliographic record
Abstract
The objectives of this study were to identify risk factors associated with i) a Mycobacterium avium subsp. paratuberculosis (MAP)-antibody milk enzyme-linked immunosorbent assay (MAP milk ELISA)-positive herd status, and ii) the within-herd MAP milk ELISA-positive prevalence in Canadian dairy herds. This prospective cohort study was conducted between 2005 and 2009 on 226 herds in Ontario and western Canada, which participated in a voluntary risk assessment (RA)-based Johne's disease control program. Two MAP milk ELISA and risk assessments and a previsit survey were available per herd. The overall farm RA scores alone could not be used to predict whether a herd would test positive for MAP antibodies. However, the results of this study indicated that increasing the likelihood of exposing calves to MAP through certain management practices, as assessed with the RA, increased the likelihood of a herd being test-positive for MAP antibodies. (MAP)-antibody milk enzyme-linked immunosorbent assay (MAP milk ELISA)-positive herd status, and ii) the within-herd MAP milk ELISA-positive prevalence in Canadian dairy herds. This prospective cohort study was conducted between 2005 and 2009 on 226 herds in Ontario and western Canada, which participated in a voluntary risk assessment (RA)-based Johne’s disease control program. Two MAP milk ELISA and risk assessments and a previsit survey were available per herd. The overall farm RA scores alone could not be used to predict whether a herd would test positive for MAP antibodies. However, the results of this study indicated that increasing the likelihood of exposing calves to MAP through certain management practices, as assessed with the RA, increased the likelihood of a herd being test-positive for MAP antibodies.
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 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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".