Bibliographic record
Abstract
Flying in the cluttered rainforest is challenging at the best of times, and it is particularly challenging for little bats when it rains. In 1971, Donald R. Griffin showed how high humidity and rain interferes with echolocation, which could explain why many bats won't fly during a downpour. In addition, having wet fur could increase the energetic costs of thermoregulation and decrease the aerodynamic properties of the bat by causing the fur to clump together. However, no one knew how much of an impact getting wet might have on bats in flight. In a recent study, Christian C. Voig and his colleagues from the Leibniz Institute for Zoo and Wildlife Research, and from the Freie Universität Berlin, Germany, measured the cost incurred by bats when flying in the rain.The researchers studied 10 Sowell's short-tailed bats (Carollia sowelli) at La Selva Biological Station in Costa Rica. Each bat was exposed to three treatments in random order. In the first treatment, the researchers allowed the bats to fly in dry conditions; the second treatment consisted of wetting the bats with tap water and then allowing them to fly; and during the third treatment, the bats were exposed to moderate rain while flying. Voig and his colleagues measured the metabolic rate of the bats before, during and after flight to determine the cost of flight during these three different conditions.The metabolic rate of dry bats while flying conformed to the team's expectations for mammals of that size. However, the metabolic rate of the wet bats was more than twice as high as that of the dry bats, and it didn't matter how the animals had been drenched.Although the additional weight of water itself could partially explain the higher cost of flying while wet, the researchers point out that a twofold increase in metabolic rate would have required the average 18 g bat to be carrying 25 g of water, which is unlikely as dry and wet bats weighed about the same. The increase in flight costs was also not due to changes in flight pattern caused by the raindrops, because the wet bats that had been doused with tap water experienced the same increase in metabolic rate as the bats that had been rained on.However, Voig and his team of researchers noticed that water caused the bats' fur to clump, which could decrease the aerodynamic properties of the fur, increasing the costs of lift and thrust during flight. They also suggest that the cooling effect of water evaporating from the bat's fur and wing membranes increases the cost of thermoregulation and could therefore increase the cost of flight.Off all living and extinct vertebrates, only three groups have evolved flight: pterosaurs, birds and bats; but of these three groups, only bats are covered with fur. Although fur aids in bats' thermoregulation by providing insulation, Voig's study shows that having fur can be a drag if you are a hungry little bat trying to forage in the rain.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".