Research and Teaching of Dairy Cattle Well Being: Finding Synergy Between Ethology and Epidemiology
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
Epidemiology is a tool used to identify and quantify risk factors that contribute to the state of health or disease. In addition, the maintenance of health and recognition of nonhuman animal welfare are both key principles of health management. Animal welfare and ethology provide important contributions to our ability to understand and improve health. As such, there can be a strong connection between the disciplines of ethology and epidemiology. This connection becomes a synergy through collaborative research. At the University of Guelph, and at other institutions, dairy health management research efforts involving collaborations between faculty trained in ethology and epidemiology have led to refined and improved research programs, improved access to funding, and a broader extension audience. Furthermore, these collaborations have enhanced teaching programs and facilitated the integration of ethology and welfare topics throughout the veterinary medical curriculum. The paper provides the basis and context for the synergy between ethology and epidemiology and describes examples of teaching and research programs built upon this synergy for the enhancement of dairy cattle well being.
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 | 0.008 | 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 | 0.001 | 0.001 |
| 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