A Field Validation of Plasma Metabolite Profiling to Assess Refueling Performance of Migratory Birds
Bibliographic record
Abstract
Plasma metabolite profiling offers a potential means to assess stopover refueling performance of migratory birds from a single capture. However, this method has not previously been validated where site quality has been determined independently using analysis of capture data. We captured and blood sampled six passerine bird species refueling at known high-quality (BASE) and low-quality (TIP) sites at Long Point, Ontario, Canada. Plasma triglyceride, an indicator of fat deposition, was higher at the BASE in three early-season species: the hermit thrush, the American robin, and the white-throated sparrow. Plasma B-OH-butyrate, an indicator of fasting and lipid utilization, was lower at the BASE in the same three species. Plasma glycerol was lower at the BASE in American robins, and plasma phospholipid did not differ between sites. No metabolite suggested better conditions at the TIP in any species. Regression of size-corrected mass on time of day also indicated better refueling performance at the BASE in some species, but metabolite profiling was generally more sensitive to site differences. The relationship between plasma glycerol and triglyceride was U-shaped, indicating high glycerol production during both lipolysis (as was previously known) and rapid fat deposition. Our results confirm the validity of metabolite profiling to assess stopover habitat quality and individual performance in refueling migrants.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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".