Reproduction and Mortality of the High Arctic Wolf, <em>Canis lupus arctos</em>, in Northeast Greenland, 1978-1998
Bibliographic record
Abstract
Reproduction and mortality of the High Arctic Wolf (Canis lupus arctos) in northeast Greenland were investigated through a temporal and spatial analysis of data on litter sizes from direct counts of pups during 21 years (1978-1998). A minimum of 22 pups were produced in a total of six areas. Overall mean litter size was 2.0 pups/litter. This was the lowest mean litter size recorded for Wolves in North America through observations of pups in summer and was probably related to low availability and vulnerability of ungulate prey. Pack size and litter size were very strongly positively correlated. Large packs (4-7 adults) produced significantly more pups than smaller packs. Mean maximum litter size from 17 North American studies employing similar methods, suggested that maximum productivity of wolves in Greenland was 58% below that of wolves elsewhere. The number of Wolf pups born in North America was negatively correlated with increasing latitude. Eight mortalities were identified and were predominantly caused by humans despite the fact that this Wolf population inhabits a national park with year-round protection.
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 | 0.000 | 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".