Missing pieces of the puzzle to effectively control digital dermatitis
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
Since the first report of bovine digital dermatitis (DD) in 1974, there is a large body of the literature published; however, effective prevention and control of the disease remain elusive. Although many aspects of the pathogenesis of DD have been investigated, even some of the most basic questions such as the aetiology of this disease remain under debate. Treponema spp. have been strongly associated with DD lesions and occur in abundance in advanced lesions; however, efforts to induce disease with pure cultures of these organisms have been largely underwhelming and inconsistent. Furthermore, although the disease has been presented for several decades, there is limited scientific evidence regarding effective treatment of DD. Apparent discrepancies between effectiveness in vitro and in vivo have challenged the scientific community to identify new potential treatment options. With no treatment resulting in a 100% cure rate, the current expectation is manageable control, but prospects for the eradication of the disease are unlikely using current approaches. In order to develop more effective approaches to control DD on-farm, there is a critical need for a deeper understanding regarding the causation, ecology, transmission and treatment of this disease. In this article, we attempt to provide insights into specific research needs related to DD in order to assist the industry, researchers, pharmaceutical companies and research sponsors with decision-making and identified research 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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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 it