Roosting behaviour and roost selection of female big brown bats (<i>Eptesicus fuscus</i>) roosting in rock crevices in southeastern Alberta
Bibliographic record
Abstract
We studied big brown bats (Eptesicus fuscus) roosting in rock crevices along the South Saskatchewan River in southeastern Alberta. We documented roosting behaviour and roost selection. During pregnancy and lactation, individuals aggregated as several small groups or one large group (maternity colony). Postlactating females roosted alone more frequently. During postlactation, individuals periodically returned to roost with a group dominated by pups, between periods of roosting alone. We identified 72 roosts used by members of the colony. Adult females switched roosts frequently and few roosts (24%) were reused. During pregnancy and lactation, the colony roosted in a 1.25-km length of the river valley on the northwest side of the river. With the onset of postlactation, females began roosting on both sides of the river and within a longer section of the river valley, and roosts faced in a more southerly direction. Crevices selected as roosts were more vertical in orientation, were farther from level ground above, and had openings that were smaller than those randomly available. Roosts used during pregnancy, lactation, and postlactation differed in physical attributes; lactation roosts were deeper and had larger openings. Selection of crevices with particular attributes suggested that selection was based on microclimate and avoidance of predation.
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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 | 0.001 | 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) | 0.001 | 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".