Vaughan, T. A., J. M. Ryan, and N. J. Czaplewski. 2011. MAMMALOGY. 5th ed. Jones and Bartlett Publishers, Sudbury, Massachusetts, 750 pp. ISBN 978-0-7637-6299-5, price (paper), $100.00
Bibliographic record
Abstract
Last summer I spent time with old friends. Terry Vaughan and company have significantly updated their text, Mammalogy, for the 5th edition (2011). The book is 62% larger than the 1st edition in 1972 (Vaughan 1972). Vaughan, Ryan, and Czaplewski skewer topics with a simplicity derived from years of mammalian research and teaching, and it is a pure pleasure to read. The synthetic nature of Mammalogy (2011) and exceptional clarity in writing make this edition an ideal book that is not just for class. Because much new research has been integrated into each chapter, all mammalogists will appreciate new introductions to each group and newly synthesized classification, ecology, physiology, and other subject-driven chapters. I found myself picking up the book where I had left off and treating it more like a novel than a text. Further, I kept interrupting myself and wandering to other topics (what's going on these days with primates, or the latest in bats, or the latest in whale evolution). It was a rich, rewarding summer.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.111 | 0.080 |
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".