North America’s Ducks, Geese and Swans in the 21st Century: A 2010 Supplement to <i>Waterfowl of North America</i>
Bibliographic record
Abstract
Since the 1975 publication of Waterfowl of North America, a great deal of ornithological literature has appeared concerning North American ducks, geese & swans. The most significant of these are the species accounts in the American Ornithologists’ Union The Birds of North America (B.O.N.A.) series, 46 of which were published between 1993 and 2003, and which include all the species known to breed in the United States and Canada (see references). Population data of wild species are constantly changing, and sometimes of limited accuracy, but long-term averages or trends are often significant. National population surveys such as the annual U.S. Fish & Wildlife Service’s Breeding Bird Surveys, and annual hunter-kill (“harvest”) surveys by the U.S. Fish & Wildlife Service and Canadian Wildlife Service are thus of both immediate and long-term interest. Text updates for the following species accounts are minimal. I have stressed apparent population trends and identified new major literature sources. I have also modified the majority of the range maps to make them more closely conform to our present-day knowledge of breeding and wintering ranges. The breeding ranges of some species are still inadequately known, such as those of the scoters, which breed in large regions of Canada and Alaska that are still only poorly surveyed. Not only have breeding ranges changed or become clearer, but also many wintering ranges have changed markedly since the 1970s, in conjunction with global warming trends (Johnsgard, 2009; Niven, Butcher & Bancroft, 2009).
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 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.078 | 0.033 |
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".