Anion Gap Correlates with Serum D- and DL-Lactate Concentration in Diarrheic Neonatal Calves
Bibliographic record
Abstract
The objective of this study was to investigate the relationship between serum D- and L-lactate concentrations, and anion gap (AG) in neonatal calves. The association of AG with lactic acidosis in diarrheic calves has only been investigated by measurement of L-lactate in calves with experimentally induced diarrhea. D-lactate has recently been reported to be present in high concentrations in the serum of some diarrheic neonatal calves. The contribution of this acid to AG is not reported. The relationship between AG and L- and D-lactate concentrations was examined in 24 healthy calves and 52 calves with naturally occurring infectious diarrhea with metabolic acidosis. AG was calculated as [Na+ + K+] - [Cl- + HCO3-]. D- and L-lactate were quantified using high-performance liquid chromatography. There was no correlation between L-lactate and AG, contrary to previous reports in the literature. Moderate correlations between D-lactate concentration and AG (r = .74, P < .0001), and between DL-lactate and AG (r = .77), P < .0001) were detected. No differences existed due to the age or sex of the calf. This study indicates that AG provides information on the nature of acidosis in the diarrheic, neonatal calf and reinforces the importance of investigating clinical, in addition to experimental, populations.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".