Welfare in dairy cattle: Epidemiologic approaches for detection and treatment of lameness
Bibliographic record
Abstract
Lameness in dairy cattle is one of the primary welfare concerns in the industry. The objectives of this thesis were to investigate the use of an accelerometer for early detection of lameness, to describe the etiology and temporal changes in hoof lesion prevalence, and to assess treatments for two types of lesions that commonly cause lameness. The Pedometer Plus™ was first validated for lying behaviour and activity measurements and determined to accurately collect data on lying and on leg movement in the cow. This system was then used to determine if changes in activity and lying behaviour could be observed during presence of hoof lesions or during lameness. Lame cows decreased their activity and increased daily lying duration compared to non-lame cows. Activity, lying duration, and lying bouts were found to be altered with particular hoof lesions compared to cows without painful lesions. Lying duration was increased in periods where cows had painful lesions compared to periods when cows had no painful lesions present on their hooves. Digital dermatitis and sole ulcers were the most commonly observed painful hoof lesions. Presence of these lesions increased the odds of a cow having that lesion later in life. Additionally, the odds of developing a sole ulcer were higher in cows that had previously had hemorrhages. A randomized clinical trial compared the use of a tetracycline hydrochloride paste to use of a bandage or no treatment in digital dermatitis lesions. Lesion healing rates did not differ between the two treatments, while both were more effective than the negative control. An algometer was used to quantify pain at the lesion site and to verify decreasing pain responses between active, healing and healed lesions. The effect of therapeutic hoof block application on sound dairy cows was assessed, with lactating dairy cows randomly assigned to receive a block (n=10) or no treatment (n=10). Block application had little effect on the activity, lying behaviour and production of sound lactating dairy cattle. Application was associated with increased gait abnormality. These results provide potential dairy cattle welfare improvement through early identification and treatment of hoof lesions and lameness.
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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 | 0.008 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".