ADSA Foundation Scholar Award: What makes for a good life for transition dairy cows? Current research and future directions
Bibliographic record
Abstract
Dairy cows experience several challenges during the transition period, historically defined as the 3 wk before to 3 wk after calving. During this 6-wk window, cows undergo a series of social, nutritional, and physical changes that affect their quality of life. Cows are also at the highest risk of becoming ill in the days and weeks after calving compared with any other period in their adult life. Because of this, the transition cow has been a central focus of dairy cattle research for at least the last 50 yr, with much of this work targeted at identifying, treating, and preventing postpartum disease. However, understanding what makes for a good life for transition cows requires consideration of more than just their health. When considering a cow's welfare, we must also include her emotional experiences and ability to live a reasonably natural life. To gain a broader perspective on the welfare of transition cows that goes beyond their health, continued inter- and transdisciplinary approaches are needed. The aims of this narrative review are to (1) describe a framework used to study animal welfare, which includes different perspectives on what makes for a good life for animals using examples from transition cow research, (2) summarize the advancements we have made in developing our understanding of the welfare of transition dairy cows over the last several decades, (3) identify gaps in the literature and propose new and continued topics for research, and (4) suggest a path forward for researchers, including the use of methods from both the natural and social sciences to rethink existing problems, understanding barriers to adoption of evidence-based practice, and prepare for future challenges.
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 | 0.011 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.063 | 0.012 |
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".