Evidence for spring stopover refuelling in migrating silver-haired bats (<i>Lasionycteris</i><i> noctivagans</i>)
Bibliographic record
Abstract
Migrating animals must acquire sufficient fuel to sustain migratory movement, but how time is allocated to achieve this can vary greatly. The fuel strategies used by migrating bats are not well understood and have not been investigated during the spring when insectivorous bats face low food abundance. Migrating silver-haired bats (Lasionycteris noctivagans (Le Conte, 1831)) were captured at a stopover site in Long Point, Ontario, Canada, in April and May of 2012–2014. We followed the movements of 40 bats outfitted with radio transmitters using an automated telemetry array and examined the effects of ambient temperature, fat stores, and sex on stopover duration. As seen previously in autumn, most bats departed the evening following capture, but one-third of bats used multiday stopovers. Extended stopover was associated with lower ambient temperature. There was no effect of sex or fat at capture on stopover departure probability. Bats captured closer to dawn had greater fat mass and lean mass than those captured early in the night, a trend indicative of fuel deposition at this site. This is the first study to provide evidence that bats use stopover habitat for refuelling.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| 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".