Graduate Student Literature Review: Integrating concepts of animal welfare and health-related quality of life for preweaning dairy calves
Bibliographic record
Abstract
Dairy calf welfare assessment tools focusing on the preweaning period have been proposed in recent research. Despite the existence of these tools, assessing the welfare and health-related quality of life (HRQoL) of dairy calves remains challenging. These difficulties may stem from the complexity of assessing all dimensions of calf welfare and the validity, reliability, and feasibility of the indicators used in assessment tools. This review aims to discuss welfare and HRQoL concepts and integrate them into a framework to facilitate the understanding of dairy calf welfare and HRQoL. The review also identifies on-farm dairy calf welfare indicators and explores how their validity, reliability, and feasibility have been evaluated. Health-related quality of life, as a component of the quality of life concept, is used to determine how an animal feels during illness using behavioral expressions of affective states. In this review, we adapted a human HRQoL framework for dairy calves, illustrating the interconnection of 3 domains of animal welfare (behavior, mental state, and health) in assessing calves' HRQoL. It is worth noting that a limited number of HRQoL assessment tools have been developed for dairy calves, and there is no standard way to assess the welfare of preweaning dairy calves. Some studies focus on specific aspects of animal welfare, whereas others address this concept more broadly. Although behavioral indicators have been explored in dairy science, they often remain disconnected from the concept of HRQoL. After reviewing various welfare assessment tools focusing on preweaning dairy calves, 44 welfare indicators were selected. Considering the selected welfare indicators, we observed that their validity, reliability, and feasibility have not been extensively explored. This review contributes to understanding welfare and HRQoL concepts for preweaning dairy calves and highlights opportunities to enhance the assessment of welfare and HRQoL for these animals.
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 | 0.003 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.013 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".