Day roost characteristics of northern long-eared bats (Myotis septentrionalis) in relation to female reproductive status
Bibliographic record
Abstract
(Uploaded by Plazi for the Bat Literature Project) In summer, females of most temperate bat species aggregate at maternity roosts, during which time females gestate, give birth, and wean offspring. These activities make the presence of suitable roosts critical for population persistence. Many studies have identified important roost tree characteristics by comparing roost trees to random trees. However, if bats select trees that facilitate either torpor use or maintenance of normothermic body temperatures relative to the energetic demands of reproduction, then it follows that roost tree characteristics may vary similarly. We compared variation in roost tree and site selection by lactating northern long-eared bats to the pre- and post-lactation periods. Scores from 2 principal components were the best predictors of the variation in roost selection. Relative to pre- and post-lactation periods lactating bat roost sites had a high and relatively open dominant canopy with low tree density (both coniferous and deciduous) and roost sites were situated high in tall trees. Our result demonstrates that when managing for bat roost trees, within-season variation in roost tree use should be considered.
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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) | 0.002 | 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".