Control of caseous lymphadenitis in sheep: Risk factors for disease and validation of an interferon-gamma assay
Bibliographic record
Abstract
This study investigated control of Caseous Lymphadenitis (CLA) by examining the validity of a whole blood interferon-gamma (IFN-[gamma]) enzyme immuno assay in determining disease status in naturally infected sheep. The assay, using formalin-inactivated whole bacterial cells as antigen, was assessed in known-negative, experimentally and naturally infected sheep. A sensitivity of 91% and specificity of 98% were observed when using a cut-off of 0.09 optical density (OD). Necropsy, revealed little correlation between test response and extent of infection, but did confirm the status of test negative animals. An algorithm was developed for the use of the assay in eradication of CLA. A mail survey of Ontario sheep producers determined that source of replacement stock, using a contract shearer and type of feeder are risk factors associated with abscess status of the flock (P<0.05). The IFN-[gamma] assay has the potential to be a useful tool in an eradication program for CLA.
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 | 0.004 | 0.010 |
| 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) | 0.000 | 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 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".