Sexual dimorphism in bat wing morphology — variation among foraging styles
Bibliographic record
Abstract
Sexual dimorphism can lead to differences in foraging style among conspecifics due to morphological differences. Within bats, maneuverability and speed of flight are influenced by wing shape and size, which may differ between sexes. Female bats gain about 30% of their body mass during pregnancy, affecting their agility and flight efficiency. To fill the same foraging niche as males, pregnant female bats would require wing size and (or) shape modifications to maintain maneuverability. We investigated sexual dimorphism in bat wing morphology and how it varies among foraging guilds. Wing photos of male and female adult bats (19 species) in Canada, Belize, and Dominica were analyzed using two-dimensional geometric morphometrics, wing loading, and aspect ratios. Nonpregnant female bats had higher wing loading than males, suggesting that they are less maneuverable than males. Additionally, mass increases during pregnancy may not permit female bats to forage as male conspecifics do. Wing shape differed minimally among foraging guilds with only frugivores differing significantly from all other guilds. Further studies should investigate how female bats forage during their reproductive cycle and determine how frugivore wings differ and whether there are individual differences in wing shape that are not consistent among bat species.
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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 | 0.000 | 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".