APPENDIX 21. AN ANALYSIS OF THE HABITAT CAPABILITY OF THE BITTERROOT ECOSYSTEM FOR GRIZZLY BEARS Public comment received on the Draft Environmental Impact Statement for Grizzly Bear Recovery in the
Bibliographic record
Abstract
Bitterroot Ecosystem indicated substantial concern about the amount and quality of habitat included in the Bitterroot area and the contribution of a restored grizzly bear population in the Bitterroot to the recovery and continued existence of grizzly bears south of Canada. Some commentors indicated that they thought that the designated recovery area was too small and did not provide sufficient habitat for the needs of a recovered population of bears. Other comments questioned the number of bears that could be supported by habitat within the wilderness and multiple use lands identified in the alternatives. A special appropriation was made by Congress for the U.S. Fish and Wildlife Service to study these issues more thoroughly in the Final Environmental Impact Statement. The four reports in this appendix apply the best available scientific approaches to answer these questions. Three reports were produced by Dr. Mark Boyce using this funding. The fourth report was produced by the Craighead Wildlife-Wildlands Institute and is included here because the information is pertinent to the question of habitat capability of the Bitterroot Ecosystem for grizzly bears. The first report, Relating Populations to Habitats using Resource Selection Functions (Appendix 21A), details a methodology to relate habitat to population size utilizing grizzly bears as an example. This methodology was specifically developed for this Bitterroot project and it has subsequently been accepted for publication in a peer reviewed scientific journal.
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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 | 0.001 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.249 | 0.055 |
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".