Predicting the Availability of Understory Structural Features Important for Canadian Lynx Denning Habitat on Managed Lands in Northeastern Washington Lynx Ranges
Bibliographic record
Abstract
Abstract Stands identified as potential Canadian lynx denning habitat by a habitat suitability model were sampled in northeastern Washington for stand structure and understory structural features identified as important for denning lynx. Potential den structures were quantified by use of strip transects, and stand structure was quantified through an enhanced forest inventory approach focused on assessing understory and downed wood conditions. Information theoretic model selection methods indicated that the best model to predict potential denning understory structure availability included downed wood abundance, total basal area, and average stand diameter. The strong predictive ability of our models suggest that understory features important to denning lynx can be predicted using traditional inventory data with the addition of a downed wood line intercept methodology. In general, our study supports the suggestion that assessing downed wood availability will effectively address concerns over quantifying the availability of understory structural features identified as being important at lynx den sites. West. J. Appl. For. 20(4):224–227.
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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 | 0.000 | 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) | 0.001 | 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".