An association between ear and tail morphologies of bats and their foraging style
Bibliographic record
Abstract
Most studies relating bat morphology to flight ecology have concentrated on the wing membrane. Here, canonical variance analysis showed that the ear and tail morphologies of bats also strongly relate to foraging strategy, which in turn is correlated with flight style. Variations in tail membrane morphology are likely to be a trade-off between increases in the mechanical cost of flight and improvements in foraging and flight performance. Flying with large ears is also potentially energetically expensive, particularly at high flight speeds. Large ears, therefore, are only likely to be affordable for slow foraging gleaning bat species. Bats with faster foraging flight styles tend to have smaller ears, possibly to cut the overall drag produced and reduce the power required for flight. Variations in the size of ears and tail membranes appear to be driven primarily by foraging strategy and not by body size, because the scaling relationships found are either weak or not significant. Ear size in bats may be a result of a trade-off between acoustic and aerodynamic performance.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.003 | 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".