Bibliographic record
Abstract
In the northeast corner of Washington State sit the Selkirk and Kettle mountain ranges. There, woodland caribou, grizzly bear, and gray wolves freely roam 1.5 million acres of spruce and fir forest, talus, and river valleys. Within this geographic area is Bunchgrass Meadows, a 711-acre (288-hectare) wetland complex within the Colville National Forest that stands out as one of the many gems on our public lands and one of the newest “Wetlands of Distinction”. Bunchgrass Meadows is at the headwaters of Harvey Creek and at the crossroads of Kootenai, Colville, Kalispel, Spokane, and Okanogan traditional tribal lands (Figure 1). This relatively high-elevation feature (about 5,084 ft., 1,550 m) is found in the Canadian Rocky Mountain ecoregion near the boundary between Washington and Idaho. Snowmelt and rain confined by the surrounding hillslopes collect and linger on a slow meander to Harvey Creek at the northeastern end, sustaining an exceptionally rich and diverse array of wetland habitats (riverine, lacustrine, slope, and depressional; Figure 2). Multiple natural resource management agencies have compiled documentation on the unique structure and composition of this wetland complex. The U.S. Forest Service (USFS) designated Bunchgrass Meadows as a Research Natural Area (RNA) in 2008. The USFS’ regional RNA Committee found Bunchgrass Meadows to be exemplary of terrestrial and wetland ecosystems, including high elevation mountain meadow,
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.011 | 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".