Frequency of Pre-partum Negative Energy Balance and Post-partum Subclinical Ketosis and the Cow- and Herd-levels in North East Dairy Herds
Bibliographic record
Abstract
Large increases in demands for energy and nutrients occur as dairy cows transition from the last weeks of pregnancy to the first weeks of lactation. If excessive, negative energy balance (NEB) in the pre-partum period and subclinical ketosis (SCK) in the post-partum period may be associated with poor reproductive and milking performance, as well as increased incidence of metabolic (e.g. DA) and infectious diseases (e.g. mastitis). Published research suggests that SCK is the most costly disorder of dairy cows in Ontario. The objective of this study was to measure the occurrence of NEB and SCK in a large sample of progressive dairy herds to determine if there is opportunity for better management of this critical time in a cow's life.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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".