Blood metabolites as indicators of nutrient utilization in fasting, lactating phocid seals: does depletion of nutrient reserves terminate lactation?
Bibliographic record
Abstract
Metabolites of lipid (free fatty acids (FFA) and β-hydroxybutyrate (βHBA)) and protein (blood urea nitrogen (BUN)) oxidation were measured during lactation in 18 female grey seals (Halichoerus grypus) and 6 female hooded seals (Cystophora cristata) as indicators of nutrient depletion and possible cues for pup weaning. FFA levels were high during lactation in both grey seals (51.2 ± 2.3 mg·dL-1) and hooded seals (67.0 ± 8.1 mg·dL-1), and levels were primarily related to the rapid lipid mobilization required for their high respective milk-fat outputs (P = 0.002). βHBA concentrations were negligible throughout lactation in both species (0.30 ± 0.14 and 0.03 ± 0.01 mg·dL-1, respectively). Grey seals exhibited a decrease in BUN levels over the course of lactation (i.e., days 0-15, 39.3 ± 1.8 - 23.5 ± 3.3 mg·dL-1, P < 0.001), which suggests protein sparing despite the added energetic cost of milk production over the 16-d lactation period. In contrast, hooded seals showed higher levels and no change in BUN levels (i.e., days 0-3, 43.2 ± 2.1 - 45.8 ± 2.1 mg·dL-1, P > 0.3), suggesting that there is less need to spare protein in a species which lactates for only 3.6 d. Females of both species weaned their pups before entering stage III fasting, therefore metabolite levels do not appear to be a physiological cue for weaning.
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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 | 0.000 |
| 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 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".