Body condition explains little of the interindividual variation in the swarming behaviour of adult male little brown myotis (<i>Myotis lucifugus</i>) in Nova Scotia, Canada
Bibliographic record
Abstract
Two competing activities of temperate insectivorous bats during the fall swarming period have direct fitness consequences: fat storage for hibernation and mating. This study investigated whether interindividual variation in body condition (as a metric of stored fat; body mass/forearm length) correlated with reproductive status and influenced swarming behaviour of adult male little brown myotis (Myotis lucifugus (Le Conte, 1831)) in Nova Scotia, Canada. We predicted that bats in good body condition would more likely be reproductive and would be more likely to remain at, and closer to, a swarming site than males in poor body condition. As predicted, males in good body condition were more likely to be in advanced reproductive states than those in poor body condition. However, contrary to the prediction, males in good body condition spent significantly less time at the swarming site than males with poor body condition. There was no difference between bats of contrasting body conditions in the probability of relocating them or how far from the swarming site they roosted. Because variation in swarming behaviours of male M. lucifugus at a swarming site was not explained by body condition, one or more other factors (e.g., social, energetic) must be important.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".