Incidence and effects of subacute ruminal acidosis and subclinical ketosis with respect to postpartum anestrus in grazing dairy cows
Why this work is in the frame
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Bibliographic record
Abstract
Subclinical Ruminal Acidosis (SARA) and Subclinical Ketosis (SCK) are two of the most prevalent metabolic diseases of dairy cows, with impacts on reproductive performance. There is scarce literature about these diseases in dairy regions in Colombia. In 29 randomly selected herds in Pasto, Colombia, 249 dairy cows were followed weekly for two months postpartum to determine: 1) incidence risk of SARA and SCK; and 2) effects of SARA and SCK on the occurrence of postpartum anestrus (PA) at two months. Samples from ruminal liquor and blood were obtained one time per cow during the first week postpartum to determine presence of SARA (pH < 5.6) and SCK (1.0-2.9 mmol/L of blood Beta-Hydroxy-Butyrate), respectively. PA diagnosis was determined with ultrasound. Pregnancy risks at 30 and 60 days post-breeding (and assumed embryo losses between these days) were determined. Risk factors associated with PA were estimated through a mixed multi-level multivariable logistic regression model, adjusting for clustering of cows within herds. The incidence risks of SARA and SCK were 23.3% and 46.2%, respectively. Simultaneous occurrence of SCK and SARA (SCASCK) was present in 5.2% of the cows. In the final multivariable model, the occurrence of SARA (Odds Ratio: OR = 39.4), SCK (OR = 47.4) and SCASCK (OR = 68.5) was associated with increased odds of PA. Feeding a transition period diet was associated with reduced odds of PA (OR = 0.15). Second parity cows had significantly lower odds of PA than first parity cows (OR = 0.21). In conclusion, inadequate pre-partum and postpartum nutritional management of the herds increased the occurrence of SARA and SCK, which had adverse effects on reproductive performance.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 it