A systematic review of the cost of ketosis in dairy cattle
Bibliographic record
Abstract
A systematic review was conducted to assess the cost of ketosis in dairy cattle, and to elucidate how ketosis cost is estimated in each of the studies. Scientific papers addressing the economic impact of ketosis in dairy cows were identified through a search in 4 databases (Medline, ISI Web of Science, CAB Abstracts, and Agricola). The literature search was conducted with no restrictions on the date of study publication, publication type, or language. The methodological quality of the studies was assessed regarding study design, data collection, and analysis and interpretation of the study results. Of 531 identified records, 10 were selected, of which 9 were published from 2015 onward. Of the 10 studies reviewed, 9 report cost of a case of ketosis, and the estimates vary widely, with values ranging from €19 to €812. Two studies report ketosis cost at a farm level (€3.6-€29/cow per year). Among the studies, we observed great variation not only in the estimation models and inputs used (costs and losses associated with the disease) but also in the definition of ketosis and its prevalence or incidence figures. Moreover, the cost of ketosis was estimated for dairy farms in the United States, Canada, the Netherlands, Denmark, France, Germany, Spain, Sweden, Norway, and India. Consequently, there was great heterogeneity regarding herd characteristics, milk production, milk prices, culled cows' value, feed prices, and costs of veterinary services. Ketosis cost estimates vary as a consequence of all these aspects. Therefore, although most of the studies were well-designed and used high-quality data, the systematic approach review does not allow combination of the cost estimates of into a single figure. In conclusion, our review highlights an overall considerable economic impact of ketosis in dairy cattle. Economic prevention and mitigation strategies should be taken according to herd- and country-specific conditions. Ketosis cost figures reported in economic studies should always be considered carefully and interpreted with appropriate consideration of the inputs of the estimation, country context, and herd parameters.
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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 | 0.013 | 0.066 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.010 |
| Bibliometrics | 0.020 | 0.017 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".