Canopy and edge activity of bats in a quaking aspen (<i>Populus tremuloides</i>) forest
Bibliographic record
Abstract
Characteristics of edges affect the behavior of species that are active in and near edges. Forest canopies may provide edge-like habitat for bats, though bat response to edge orientation has not been well examined. We sampled bat activity in quaking aspen ( Populus tremuloides Michx.) forest canopies and edges in Heber Valley, Utah, during summer 2009 using Anabat detectors. Categorization and regression tree (CART) analysis of echolocation characteristics (e.g., frequency, duration) identified two guilds based on characteristic frequency (i.e., high- and low-frequency guilds). We used linear regression to compare characteristics of canopy and edge vegetation (e.g., tree height, diameter at breast height) to bat activity levels. Activity levels of high-frequency bats did not respond differentially to edge vegetation; low-frequency bat activity seemed to respond to canopy height. Activity levels of high-frequency bats were significantly greater than low-frequency bats in both edges and canopies. We detected significantly more bat activity in forest edges than in forest canopies, indicating the importance of edges to bats in forests.
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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) | 0.000 | 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".