Estimating plasma volume in neonatal Holstein calves fed one or two feedings of a lacteal-based colostrum replacer using Evans blue dye and hematocrit values at various time points
Bibliographic record
Abstract
Cabral, R. G., Chapman, C. E., Kent, E. J. and Erickson, P. S. 2015. Estimating plasma volume in neonatal Holstein calves fed one or two feedings of a lacteal-based colostrum replacer using Evans blue dye and hematocrit values at various time points. Can. J. Anim. Sci. 95: 293–298. Twenty-eight Holstein calves were blocked by birth date and randomly assigned to one of two treatments to investigate the effect of colostrum replacer (CR) feeding regimen on plasma volume (PV). Treatments were: (1) one feeding of CR (C1; 3 L of reconstituted CR 675 g of powder providing 184.5 g of IgG at birth) or (2) two feedings of CR (C2; 2 L of reconstituted CR at birth and 1 L of reconstituted CR at 6 h). By 6 h of age, all calves had received 3 L of CR providing 184.5 g of IgG. Plasma volume was estimated at 6, 12, 18, and 24 h after birth using Evans blue dye. No treatment effects were noted at any time points (P>0.05). Mean PV for all calves regardless of treatment at 6, 12, 18, and 24 h were 78.6, 89.2, 83.9, and 90.7 mL kg−1 of body weight, respectively. Plasma volume was correlated with hematocrit (HCT), initial HCT, and treatment. Hematocrit was correlated with PV, initial HCT, and body weight. Hematocrit for 6, 12, 18 and 24 h after birth can be predicted with an initial precolostral HCT determination.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 | 0.001 |
| 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".