Effect of Diet Composition on Plasma Metabolite Profiles in a Migratory Songbird
Bibliographic record
Abstract
Abstract Abstract Plasma metabolites provide information about the physiological state and fuel use of birds, and have been used for predicting refueling rates of birds during migratory stopovers. However, little is known about the effect of diet on metabolite concentrations in small songbirds. We investigated the effect of dietary macronutrient composition on lipid and protein metabolites in captive White-throated Sparrows (Zonotrichia albicollis). Birds fed a high-protein, low-carbohydrate insect diet had lower plasma triglyceride concentrations and higher plasma B-hydroxybutyrate concentrations than birds fed a high-carbohydrate, low-protein grain diet during feeding. The insect-fed birds also had higher plasma uric acid concentrations than grain-fed birds and birds fed a low-protein, high-fat, and high-carbohydrate fruit diet. Diet did not significantly influence plasma concentrations of glycerol or nonesterified fatty acids. After subsequent overnight fasting, birds in all three diet groups had similar concentrations of lipid metabolites, but uric acid was marginally elevated in insect-fed birds. Given that dietary macronutrient composition affected certain plasma metabolite concentrations in sparrows, investigators should consider such diet effects when using these metabolites to estimate refueling rates of free-living migratory songbirds, particularly in species that exhibit dietary plasticity during migration.
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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) | 0.001 | 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".