Bibliographic record
Abstract
are some of the world's most charismatic and controversial animals, capturing the imaginations of their friends and foes alike. Highly intelligent and adaptable, they hunt and play together in close-knit packs, sometimes roaming over hundreds of square miles in search of food. Once teetering on the brink of extinction across much of the United States and Europe, wolves have made a tremendous comeback in recent years, thanks to legal protection, changing human attitudes, and efforts to reintroduce them to suitable habitats in North America. As wolf populations have rebounded, scientific studies of them have also flourished. But there hasn't been a systematic, comprehensive overview of wolf biology since 1970. In Wolves, many of the world's leading wolf experts provide state-of-the-art coverage of just about everything you could want to know about these fascinating creatures. Individual chapters cover wolf social ecology, behavior, communication, feeding habits and hunting techniques, population dynamics, physiology and pathology, molecular genetics, evolution and taxonomy, interactions with nonhuman animals such as bears and coyotes, reintroduction, interactions with humans, and conservation and recovery efforts. The book discusses both gray and red wolves in detail and includes information about wolves around the world, from the United States and Canada to Italy, Romania, Saudi Arabia, Israel, India, and Mongolia. Wolves is also extensively illustrated with black and white photos, line drawings, maps, and fifty color plates. Unrivalled in scope and comprehensiveness, Wolves will become the definitive resource on these extraordinary animals for scientists and amateurs alike. An excellent compilation of current knowledge, with contributions from all the main players in wolf research. . . . It is designed for a wide readership, and certainly the language and style will appeal to both scientists and lucophiles alike. . . . This is an excellent summary of current knowledge and will remain the standard reference work for a long time to come. Stephen Harris, New Scientist This is the place to find almost any fact you want about wolves. Stephen Mills, BBC Wildlife Magazine
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.276 | 0.175 |
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".