A Longitudinal Field Trial of the Effect of Biotin on Lameness in Dairy Cows
Bibliographic record
Abstract
A longitudinal prospective intervention study investigated the effect of biotin supplementation on the incidence (new cases per day) of visible lameness in milking cows and heifers on five commercial farms in Gloucestershire, United Kingdom. The trial lasted from June 1997 to April 1999. Each farm participated in the trial for 18 mo. Within each herd the cows were randomly allocated to either receive a supplement of 20 mg of biotin per day or not. All cows were run as one herd on each farm. When a lame cow was identified, the farmer called one of six veterinarians to examine and treat the affected animal; findings were recorded on a standard form. A veterinarian also carried out a bimonthly locomotion assessment to ensure that all lame cows were diagnosed. There were a total of 900 cows, 1120 cow years, in the trial. The overall incidence rate of lameness (per 100 cows per year) was 68.9, with a range of 31.6 to 111.5 per farm. The incidence rates of the four most frequently reported causes of lameness were sole ulcer, 13.8; white line separation, 12.7; digital dermatitis, 12.0; and interdigital necrobacillosis, 7.1 per 100 cows per year. There was a significant difference in the incidence rate of these four lesions between supplemented and unsupplemented cows on two of the five farms, with a significant decrease in lameness in the cows supplemented with biotin. When all the farms were pooled, the risk of lameness caused by white line separation in cattle supplemented with biotin was approximately halved (Cox proportional hazard survival analysis hazard ratio = 0.57).
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".