Bibliographic record
Abstract
Abstract American black bears ( Ursus americanus ) require suitable den sites that provide security and cover to successfully survive the winter denning period. On Vancouver Island, British Columbia, Canada, black bears prefer to use cavities associated with large‐diameter hollow trees or structures derived from trees (i.e., cavities in or under logs, root boles and stumps) as den sites. Extensive harvesting of coastal forests has reduced the availability of natural den structures such that their supply may affect population sustainability. I attempted to develop new methods to address the declining supply of denning opportunities by creating and testing new den structures constructed in trees, stumps and from plastic. Between 2014–2021, I created or deployed and monitored 17 potential den structures in 2 study areas that were believed to have low den supply. I documented up to 51 visits by bears at each structure; every one of the video‐monitored structures was investigated at least 5 times. None of the plastic artificial den structures were used by bears, but an enhanced natural structure was used as a den over 4 consecutive winters. My work indicates that bears will find and investigate all natural or artificial denning structures in their environment, but artificial structures do not appear to be a viable method to mitigate losses of dens caused by forest harvesting.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 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".