Abundance, social organization, and population trend of the arctic wolf in north and east Greenland during 1978–1998
Bibliographic record
Abstract
Abundance, social organization, and population trend of the arctic wolf ( Canis lupus arctos Pocock, 1935) in north and east Greenland, 1978–1998, were determined from 353 sightings of 552 wolves by the Danish military, by expeditions, and from 8 consecutive years (1991–1998) of fieldwork. Available evidence suggested that this wolf population consisted of up to 55 wolves in favorable times. Six core packs were identified. Maximum wolf density was estimated at 1 wolf/3745 km2, which appears to be the lowest wolf density reported, representing 3.5% of maximum late winter wolf density in Denali Park, Alaska, and <1% of that in north-central Minnesota. Social organization was characterized by a preponderance of pairs and lone wolves. Mean early winter pack size was 2.6 wolves/pack; the lowest reported for wolves in North America. Packs >4 wolves were rare, constituting 3.8% of early winter sightings. The population increased, on average, 8% per year during the period 1978–1991 and appeared to reach a peak in 1991–1992. These depressed population characteristics are likely the consequence of the lowest ungulate prey availability in North America, e.g., 2.6% of that of wolves in northeastern Minnesota.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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".