Bibliographic record
Abstract
The scientific study of wolf behavior in North America is a recent development. In the early twentieth century published information was based on the observations of government trappers hired between 1915 and 1940 to eliminate the wolf as a threat to livestock. Popular literature of the time portrayed the woIf as dangerous, not only to livestock, but to game animals—and humans as well. Stanley Young of the U.S. Biological Survey wrote two books detailing the war on wolves (The Wolf in North American History) and their behavior (Wolves of North America, pt. 1.). The latter was the standard work, though inaccurate, for thirty years. When the wolf was eliminated as a threat to livestock, concern remained that it was detrimental to game species. Concern about the wolf in Mount McKinley National Park led to the classic study by Adolph Murie, based on the observation of an unmolested pack at their den site. He also was the first to quantify his data on wolf kills based on the recovered skulls and bones of prey species. 'The Wolves of Mount McKinley was published in 1944. Other studies by researchers in Canada and northern Minnesota analyzing wolf scats and kills were conducted in the 1950's, but it remained difficult to document the wolves ' effect on prey species. Douglas Pimlott began the study of wolves and their prey in Algonquin Park in Ontario in 1958. This
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.299 | 0.158 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".