Bibliographic record
Abstract
This paper reviews recent research on lameness in dairy cows, with special focus on our work at the University of British Columbia addressing the scientific assessment of impaired gait, and how such impairments can be prevented through improvements in housing. Subjective gait scores can vary considerably between observers, but the reliability of these scores can be much improved with training and the use of well-defined scoring criteria. Some variation in gait relates to hoof pathologies and pain, factors typically considered central to the problem of cattle lameness. However, many cows with impaired gait have no visible sole lesions, and vice versa, and treating lame cows with analgesics has a significant but minor effect on gait. Gait also varies with features of the cow not related to lameness (e.g. udder fill) and with features of the environment (e.g. walking surface). Most importantly, lameness (as evidenced by impaired gait) can be dramatically reduced through improvements in housing conditions, including access to pasture or to more comfortable free stalls.
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 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".