Bibliographic record
Abstract
Writing expressly for this splendid new book, 44 of America's leading naturalists describe the ornithological attractions of their favorite haunts in the United States and Canada.More than a field guide, the volume provides first-hand experiences enlivened with personal anecdotes and touches of humor, 50 line drawings by celebrated bird artist John Henry Dick, and vital information on locating both common and rare species.Every bird-watcher--armchair or field--will be delighted with the rich experiences and the delightful narratives of the contributors.Every area of the U.S. and Canada is covered; Down East in Maine (Allan D. Cruickshank); The Florida Keys (Robert Porter Allen); Great Smoky Mountains National Park (Arthur Stupka); The Black Hills of South Dakota (Herbert Krause); The Pribilofs (Roger Tory Peterson);.Ontario's Algonquin Park (Fred Bodsworth); The Black Mesa Country of Oklahoma (George Miksch Sutton); The New York City Region (John Bull); and much, much more.From the Atlantic to the Pacific, from the Rio Grande to Hudson Bay, you'll find many hours of pleasure and profit in this unusual volume.Over 440 pages, illustrated, 6 •" x 81/2 ", $7.50.EXAMINE FREE FOR 10 DAYS.Send the coupon today and en-• joy The Bird Watcher's America at home for 10 days, with no obligation to buy.If you're not delighted with it, return it for a full refund.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.936 | 0.926 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".