Effect of Transition from Conventional Milking to Robotic Milking on Teat Skin and Teat End Condition
Bibliographic record
Abstract
Effects of ketosis on reproduction were reviewed and summarised according to meta-analysis methods.Thirteen peer-reviewed papers in English based on data issued after 1960 from dairy intensive regions were selected.Summary estimates and 95% confidence intervals were calculated according to general variance-based methods for meta-analysis.Possible reasons for heterogeneity of the results were investigated among origin of the data and study design.Clinical ketosis and ketosis diagnosed by a test for ketone bodies in milk or blood were considered separately.Effects varied widely between studies.Summary estimates [95% CI] of effects of clinical ketosis were 2.5 [1.0, 4.1] more days to first service, 3.8 less % conception at first service, 5.9 [3.0, 8.8] more days to conception, 0.13 [0.06, 0.19] more services per conception, and a hazard ratio of 0.87 [0.82, 0.91] to conceive between 56 and 120 days postpartum.Different thresholds were used in studies detecting ketotic cows by a test.Results were discrepant and studies with the lowest thresholds concluded in the highest effects.Clinical cases are more likely to be detected and treatment probably contributes to limit their effect.In Holstein cows from US or Canada herds, no significant effect was evidenced.In Swedish Red and White and Swedish Friesian cows, effects were small or non significant.The highest effects were evidenced in Finncattle, Finnish Friesian or Finnish Ayrshire cows.Results suggest that under current farming conditions, effects of ketosis on reproduction are on average limited, but show large variations in different production systems.
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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 | 0.007 | 0.017 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.036 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".