GIS-based model to support programmatic section 7 consultations on the Canada lynx in Colorado
Bibliographic record
Abstract
The Colorado Department of Transportation (CDOT), on behalf of the Federal Highway Administration (FHWA), is in the process of conducting programmatic section 7 consultations on the Canada lynx. CDOT divided Colorado into eight consultation units where lynx habitat and highways intersect. A programmatic is nearing completion for one of the units; others will be developed in order of priority. The programmatic builds on the idea that the highest conservation needs for lynx, such as structures that allow it to cross roads, are not necessarily located within project limits. The programmatic therefore identifies locations that form the greatest barriers to movement, develops conservation measures for those areas, and provides agreements between the U.S Fish and Wildlife Service (FWS), FHWA, and CDOT to implement those measures. To assess barriers to movement and other conservation needs, CDOT, with the assistance of the remote sensing unit of the U.S. Bureau of Reclamation and the FWS, constructed a GIS-based model of lynx habitat. The model is designed to identify likely movement corridors and their intersection with roadways. It was assembled using detailed watershed-based vegetation maps (developed by the US Bureau of Land Management and the Colorado Division of Wildlife), digital elevation models, as wells as slope and aspect data. The process yielded several potential corridors. Their intersection with roadways was verified on the ground. CDOT then developed design recommendations for structures that connect lynx movement corridors across a highway. When constructed, these crossings will compensate for impacts associated with highway projects in the consultation unit and form the basis for a programmatic section 7 consultation.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.015 | 0.001 |
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".