Bibliographic record
Abstract
The Minnesota wolf (Canis lupus) population was estimated by the Minnesota Department of Natural Resources at 2,450 during winter 1997-1998 and had increased at an average annual rate of 4.5°% since winter 1988-1989. The population may be removed from the federal endangered species list by 2002, and management would then return to the state. A federal recovery team recommended a population goal of 1,250-1,400 wolves for Minnesota, with none in the agricultural region. A plan approved by the Minnesota legislature, however, continues the protection of wolves, except for pet and livestock depredation control, for at least 5 years after delisting. I compare number of wolves of the 1997-1998 population that would have to be killed each year by humans for various types of control versus numbers if the population continued to expand. For the 1997-1998 population, those numbers are in addition to natural mortality, depredation control, and illegal and incidental take at least 1 10 wolves and probably many more to limit wolf range, 685-1,149 wolves for sustained yield, and 929-1,956 to reduce the population. Given conservative assumptions, continued livestock depredation control, and a 4.5% rate of population and range increase as occurred during the past decade, comparable figures for 2007 are at least 171 wolves to limit range expansion, 1,064-1,786 for sustained yield, and 1,444-3,042 to reduce the population. The trend in the population since 1997-1998 is unknown, but these numbers illustrate the magnitude of the potential problems that could arise in managing Minnesota's wolves under various scenarios.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".