Bibliographic record
Abstract
Grazing management on the Great Plains has been criticized for not more closely matching the presumed grazing patterns of bison. The critics assume that bison "flash grazed," that is, grazed heavily for a short time, then moved on, and did not return for months or even years. This assumption complements the traditional view of an annual north-south migration of the herds. However, evidence from explorers' and other travelers' journals contradict both flash grazing and annual north-south migration. In a few cases where prolonged continuous observations were made in the same favorable habitat, bison were seldom absent. In Canada, bison sometimes moved from the plains into the bordering aspen parklands during severe winter weather, but not regularly and not north-south. Throughout the Great Plains, bison numbers were so great and so thoroughly spread over the country that if a herd moved on, they were quickly replaced by another, giving little opportunity for rest or regrowth of the plant communities. Bison appeared to move in response to local conditions of forage availability, as influenced by weather, fire, and previous grazing. In at least one case, bison remained on a depleted watershed until they starved, rather than moving to an adjacent watershed with adequate forage.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.002 | 0.005 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.014 | 0.002 |
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".