Short communication: Estimation of genetic parameters for gait in Canadian Holstein cows
Bibliographic record
Abstract
Lameness is one of the most important welfare and economic problems in modern dairy herds. In addition to environmental factors, lameness is affected by genetics and thus, long-term improvement of lameness can be accomplished through genetic selection. The objective of the study was to estimate the genetic parameters of a validated gait score and specific gait attributes for Holstein cows from a university dairy research herd. Two hundred thirty-three cows were gait scored multiple times over time (n=1,664 records) in different experiments using a 1-to-5 numerical rating system (NRS). One hundred seventy-two cows (n=657 records) also had 6 gait attributes scored using a 100-unit continuous visual analog scale (back arch, head bob, tracking up, joint flexion, asymmetric gait, and reluctance to bear weight). Single-trait linear animal models were used to estimate the heritability of NRS and each gait attribute, whereas a multivariate linear animal model was used to estimate genetic correlations between traits. The NRS and the gait attributes deteriorated with parity, and the scores for NRS, back arch, joint flexion, and asymmetry of the steps increased rapidly in early lactation. The heritability estimate (±SE) for NRS was 0.09±0.09. Four of the gait attributes (reluctance to bear weight, head bob, tracking up, and asymmetry of the steps) had higher heritability than NRS, ranging from 0.11±0.13 to 0.42±0.15, whereas back arch showed no genetic variation. However, the small sample of animals resulted in large standard error of the estimates. The genetic correlations between NRS and the gait attributes were >0.70, whereas the genetic correlations among the different gait attributes ranged from 0.14 to 0.92. In conclusion, NRS and most gait attributes showed genetic variation, indicating the opportunity to improve gait through genetic selection. Some specific gait attributes were more heritable than NRS and were genetically correlated with NRS. Further research with a larger population is needed to assess whether specific gait attributes would be suitable candidate traits to consider in genetic evaluations in the future.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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 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".