Habitat Evaluation Procedures (HEP) Report; Beaver Lake, Technical Report 2005.
Bibliographic record
Abstract
On August 14, 2003, the Habitat Evaluation Procedure (HEP) was used to determine baseline habitat suitability on the Beaver Lake property, an acquisition completed by the Kalispel Tribe of Indians in November 2002. Evaluation species and appropriate models include bald eagle, black-capped chickadee, Canada goose, mallard, muskrat, yellow warbler, and white-tailed deer. Habitat Suitability Index (HSI) values were visually estimated and agreed upon by all HEP team members. The Beaver Lake Project provides a total of 232.26 Habitat Units (HUs) for the species evaluated. Conifer forest habitat provides 136.58 HUs for bald eagle, black-capped chickadee, mallard, and white-tailed deer. Forested wetland habitat provides 20.02 HUs for bald eagle, black-caped chickadee, mallard, and white-tailed deer. Scrub-shrub wetland habitat provides 7.67 HUs for mallard, yellow warbler, and white-tailed deer. Grassland meadow provides 22.69 HUs for Canada goose and mallard. Emergent wetlands provide 35.04 HUs for Canada goose, mallard, and muskrat. Open water provided 10.26 HUs for Canada goose, mallard, and muskrat. The objective of using HEP at the Beaver Lake Project and other protected properties is to document the quality and quantity of available habitat for selected wildlife species. In this way, HEP provides information on the relative value of the same area at future points in time so that the effect of management activities on wildlife habitat can be quantified. When combined with other tools, the baseline HEP will be used to determine the most effective on-site management, restoration, and enhancement actions to increase habitat suitability for targeted species. The same process will be replicated every five years to quantitatively evaluate the effectiveness of management strategies in improving and maintaining habitat conditions while providing additional crediting to BPA for enhanced habitat values.
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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 | 0.006 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.064 | 0.028 |
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".