Preparatory work for the development of a scientific opinion on the main welfare risks related to the farming of sheep for wool, meat and milk production
Bibliographic record
Abstract
This report contains the results of a scoping review of sheep welfare studies and a systematic review of the effect of extensive/outdoor/migratory management on lameness compared to intensive/indoor management systems in sheep raised for the production of meat, milk, or wool in Europe. The scoping review allowed identifying and mapping 679 citations relevant to sheep welfare. Those citations were mapped according to the study population, 8 main welfare determinants (management, environment, genetics, nutrition/feeding/watering, behaviour, health, housing, handler traits/human-animal bond) and outcomes. Such mapping supported the WG in identifying gaps of knowledge and data that further led to seeking for experts' knowledge, as well as to identify areas where a systematic literature process could be performed. The systematic review that followed the scoping review provided evidence that the management system is not associated with the prevalence or risk of lameness. However, higher stocking densities were associated with prevalence or risk lameness. The body of work may appear to be quite small, however, given the difficulties faced by researchers investigating this topic, identifying studies that looked at these factors in a limited region of the world is a reasonable body of work. This is a difficult topic to study as the exposures are variable and the outcomes difficult to measure in production systems as they can occur year round and have numerous causes.
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 | 0.129 | 0.374 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.005 | 0.006 |
| Bibliometrics | 0.019 | 0.010 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.017 | 0.014 |
| Open science | 0.005 | 0.015 |
| Research integrity | 0.013 | 0.010 |
| Insufficient payload (model declined to judge) | 0.134 | 0.053 |
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".