Measurement of glomerular filtration rate during flight in a migratory bird using a single bolus injection of FITC-inulin
Bibliographic record
Abstract
During migration, passerine birds typically complete a series of multi-hour flights, each followed by a period of stopover. During flight, rates of respiratory water loss are high, yet these birds show no signs of dehydration after flights. During stopover, birds become hyperphagic to replenish fat reserves, often consuming food with high water content, such as fruit. Thus migratory birds seem to face an osmoregulatory challenge; they must reduce water losses during flight but retain the ability to excrete large quantities of water while maintaining osmotic balance at stopover. Our goal was to measure glomerular filtration rate (GFR) and fractional water reabsorption (FWR) of a migratory bird in free flight, at rest, and during feeding to assess the role of the kidney in maintaining water balance during migration. We used FITC-inulin and one- and two-phase exponential decay models to first validate a technique and then measure GFR in the Swainson's thrush, a small (∼30 g) songbird. Single-phase exponential decay models and the modified slope intercept method overestimated GFR by 26% compared with two-phase exponential decay models. We found no differences in GFR among fed, resting and flying birds, but FWR was significantly higher in resting and flying birds relative to feeding birds. There was no effect of the rate of respiratory water loss on GFR or FWR in flight. These data support the idea that birds in flight do not dramatically alter GFR but rely on increased FWR to minimize excretory water losses.
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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 | 0.001 | 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".