RECORDS OF THE EASTERN RED BAT ON THE NORTHERN FRONT RANGE OF COLORADO
Bibliographic record
Abstract
Although common in deciduous forest throughout the Midwest and east-central states, the eastern red bat (Lasiurus borealis) is rare in Colorado (Armstrong et al. 1994, Fitzgerald et al. 1994). However, this species has the potential to extend its range because belts of eastern deciduous forest habitat have expanded across western prairies and reached the Front Range of Colorado over the last 100 years (Knopf 1986). The eastern red bat ranges from Canada southward across the United States to northeastern New Mexico with most records occurring east of the Continental Divide (Hall 1981, Shump and Shump 1982, Cryan 2003). The historical range of the eastern red bat in Colorado extends along the riparian forest habitat of the South Platte and Arkansas rivers of eastern Colorado as far west as Boulder and Pueblo counties, respectively. Previous records of this species in Colorado are either individual animals caught incidentally or those submitted by the public to the Colorado Division of Public Health and Environment that lacked accurate location information (Armstrong et al. 1994). Everette et al. (2001) tentatively identified the presence of red bats on the outskirts of Denver, Colorado as recently as 2 and 7 July 1997, based on four echolocation calls recorded with Anabat detectors. Despite extensive mist netting, no red bats were captured. No new records have been reported for this species in Colorado since that time.
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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 | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".