Quantification of foot lesions and an evaluation of early detection methods for lameness in Ontario dairy farms
Bibliographic record
Abstract
This thesis is an investigation of the prevalence, risk factors, detection methods, and associations with productivity of foot lesions diagnosed during a routine hoof trimming. The project utilized 5 hoof trimmers to record lesions on 13,530 cows in 204 Ontario dairy herds from March 2004 to May 2005. Prevalence estimates were determined for 11 different lesions. Infectious lesions were most common in both tie stall and free stall housing systems. In free stall housing systems, 46% of cows had a foot lesion, compared to 26% of cows in tie stall barns. For different foot lesions, risk factors associated with increased herd level lesion prevalence included frequency of alley scraping, and year round access to an exercise area in free stalls. In tie stalls, risk factors included access to an exercise area, routinely spraying feet, larger herds, wood bedding material and number of cows trimmed. In free stalls, an association with decreased herd level lesion prevalence was found for depth of bedding and trimming heifers prior to calving. Hoof horn lesion such as ulcers, hemorrhage (HEM) and white line lesions (WLS) were associated with both differences in milk production and increased culling. The nature of the association between hoof horn lesions and milk production varied with the time relative to hoof trimming. An association with increased milk production was found prior to hoof trimming for cows with a sole ulcer, WLS and heel horn erosion. After hoof trimming, associations with decreased milk production were found for these same lesions plus HEM, interdigital korns and foot rot. All hoof horn lesions were associated with an increased culling risk (hazard ratios 1.2-1.7). The relationship between foot lesions and 3 visual lameness scoring systems were evaluated including leg score, back arch and locomotion scoring. Of the 3 systems evaluated, only locomotion scoring had a moderately useful sensitivity and specificity. However, there was a significant effect of observer on test performance resulting in differing sensitivities (61% vs 21%) and specificities (71% vs 76%).
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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".