Multiblock Analysis of Risk Factors and Management Areas of Calf Mortality in Large-Scale Dairy Herds
Bibliographic record
Abstract
Despite an abundance of available research, calf mortality persists as a multifaceted phenomenon that presents ongoing challenges in practical management. This historical single-cohort study was conducted to provide a more comprehensive layer of knowledge to the existing information pool on calf mortality risk factors by using multiblock partial least squares analysis. The method reveals the contribution of several variables aggregated into thematic blocks and allows to include multiple outcome variables describing the same phenomenon. Such an analysis of the data provides valuable information to farmers, veterinarians, and advisors alike, not only about single risk factors, but also about management areas to prioritize when tackling calf mortality. Data was gathered from 118 Estonian dairy herds, each comprising ≥100 cows, via questionnaire, sample collection, and on-farm scoring and measurements. The final dataset included 147 questions divided into 13 meaningful blocks. The outcome variables were annual herd-level calf mortality risk during the first 21 days (MR21) and 22-90 days (MR90) using farm records and the national cattle database, respectively. The average MR21 was 5.9% (median 4.4%, range 0.0-26.8%) and the average MR90 was 2.7% (median 2.3%, range 0.0-12.7%). Of the 13 thematic variable blocks, the most important blocks explaining calf mortality were 'Routine stress-inducing activities', 'Herd characteristics', 'Calving management', 'Calf housing during 5-21 days', and 'External biosecurity'. The most influential single variables associated with higher overall calf on-farm mortality during the preweaning period were poorer cleanliness scores of calving animals and calves having access to an outdoor area during the first 21 days of life. Detected risk factors for MR21 were calf barn age > 20 years, allowing the calves to suckle the first colostrum, bucket feeding calves during the first three weeks, disbudding all calves (compared to only heifer calves), and disbudding at 21-29 days of age. Risk factors for MR90 included the use of automatic milk feeders and feeding waste milk during the first three weeks, early introduction of calves to large group pens and higher in-pen age differences, absence of forced ventilation during the first three weeks, opportunity for feces to spread between calf pens, and use of calving pens for sick animals. Washing and disinfection of newborn calves' pens and testing colostrum quality were protective factors against both MR21 and MR90. Other protective practices for MR21 were related to proper colostrum feeding routines, whereas lower MR90 was mostly associated with efficient external biosecurity practices and vaccination programs. The multiblock model proved to be beneficial in providing a broader understanding of the importance of different management areas on calf mortality.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".