Review of <i>Birds of Prey of the West: A Field Guide,</i> by Brian K. Wheeler
Bibliographic record
Abstract
Birds of prey epitomize much of what attracts us to birding. Many are large and easy to observe, particularly in open landscapes. Their predatory nature and behavior give them an added aura of wildness; their migrations can be spectacular. And even veteran birders should enjoy the challenge of identifying the myriad of plumage variations shown by different ages, sexes, subspecies, and color morphs. With his newest effort, Birds of Prey of the West, Brian Wheeler has compiled a comprehensive and enhanced field guide with illustrations that stunningly capture that variation, combined with enough additional context to make it a valuable desk reference for birders of all levels. The geographic scope of this book is the United States north of Mexico and west of the Mississippi River, and Canada west of Manitoba and the western shore of Hudson Bay, north into Nunavut and across western Canada and Alaska. It covers nearly all the regularly occurring raptors of North America, excluding only the Snail Kite (Rostrhamus sociabilis) of the southeast and a few species of Eurasian and Mexican vagrants (e.g., Steller’s Sea Eagle [Haliaeetus pelagicus] and Roadside Hawk [Rupornis magnirostris]). As such, it may appeal to birders beyond the geography covered, although a companion volume is also available for the East (Wheeler 2018). This informative, richly illustrated book certainly deserves a place on the bookshelf of anyone interested in birds of prey or in the intricacies of bird identification in general.
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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.034 | 0.030 |
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".