Knowledge gaps that hamper prevention and control of<i>Mycobacterium avium</i>subspecies<i>paratuberculosis</i>infection
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
In the last decades, many regional and country-wide control programmes for Johne's disease (JD) were developed due to associated economic losses, or because of a possible association with Crohn's disease. These control programmes were often not successful, partly because management protocols were not followed, including the introduction of infected replacement cattle, because tests to identify infected animals were unreliable, and uptake by farmers was not high enough because of a perceived low return on investment. In the absence of a cure or effective commercial vaccines, control of JD is currently primarily based on herd management strategies to avoid infection of cattle and restrict within-farm and farm-to-farm transmission. Although JD control programmes have been implemented in most developed countries, lessons learned from JD prevention and control programmes are underreported. Also, JD control programmes are typically evaluated in a limited number of herds and the duration of the study is less than 5 year, making it difficult to adequately assess the efficacy of control programmes. In this manuscript, we identify the most important gaps in knowledge hampering JD prevention and control programmes, including vaccination and diagnostics. Secondly, we discuss directions that research should take to address those knowledge gaps.
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.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| 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 it