Assessing the welfare of dairy calves: outcome-based measures of calf health versus input-based measures of the use of risky management practices
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
Abstract The mortality and morbidity of unweaned dairy calves and management practices that may impair calf health and welfare were surveyed on 115 farms in Canada (Quebec) and 60 farms in Central Europe (Austria and Germany) to examine whether outcome-based measures of calf health could be used to identify farms that use management practices that place calf health at risk. Quebec herds had higher juvenile mortality incidence than those in Central Europe. Juvenile mortality was poorly estimated by producers. Low levels of mortality did not include low levels of morbidity in the same herds. Health status was not necessarily associated with management practices generally recommended for health and welfare. Many management practices that may impair calf health and welfare were found in Quebec while only some were found in Central Europe; these were related to calving management and care of the newborn, colostrum management, calf-dam separation, calf feeding, weaning and calf housing. Inadequate recording of calf morbidity and mortality can be a problem in using recorded measures to assess the level of calf health on a farm. The recorded mortality and morbidity do not necessarily show the extent that producers use management practices that pose a risk to calf health.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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