PANEL 5: BEARS AND HUMAN BEINGS Conservation of the Grizzly- Ecologic and Cuttural Considerations
Bibliographic record
Abstract
The idea that before settlement the grizzly occurred fa r ac ross the prai r ie eastward of the Rocky Mountains has prevailed for a long time (Seton 1929; Hall & Kelson 1959). Since the geographic distribution of a species is a matter of ecologic significance, i t may be worthwhile to examine this information. It is recognized, of course, that a line on a map demarking the outer limit of a distribution in any direction does not represent necessarily either a continuous o r static situation. The distribution of a species not only will be in accordance with i t s habitat, but also the extremistics of this will vary time--and--place-wise according to prevailing conditions. These often a r e most variable at a range periphery. My concern in this paper is with the distribution of the g.rizzly bear on the prai r ie east of the rocky Mountains from Canada's Saskatchewan River south-ward to the Arkansas River in the United States. For information bearing on this matter, recourse was taken to a part of our heritage of historical l i tera-ture, which is the source of an abundance of little used natural history informa-
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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.007 | 0.003 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.012 | 0.008 |
| Insufficient payload (model declined to judge) | 0.065 | 0.007 |
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".