<i>Birds of the Rocky Mountains</i>—Species Accounts, pages 76–109: Swans, Geese and Ducks
Bibliographic record
Abstract
Tundra (Whistling) Swan (Cygnus columbianus) Trumpeter Swan (Cygnus buccinator) Greater White-fronted Goose (Anser albifrons) Snow Goose (Chen caerulescens) Ross' Goose (Chen rossii) Canada Goose (Branta canadensis) Wood Duck (Aix sponsa) Green-winged Teal (Anas crecca) American Black Duck (Anas rubripes) Mallard (Anas platyrhynchos) Northern Pintail (Anas acuta) Blue-winged Teal (Anas discors) Cinnamon Teal (Anas cyanoptera) Northern Shoveler (Anas clypeata) Gadwall (Anas strepera) Eurasian Wigeon (Anas penelope) American Wigeon (Anas americana) Canvasback (Aythya valisineria) Redhead (Aythya americana) Ring-necked Duck (Aythya collaris) Greater Scaup (Aythya marila) Lesser Scaup (Aythya affinis) Harlequin Duck (Histrionicus histrionicus) Oldsquaw (Clangula hyemalis) Black Scoter (Melanitta nigra) Surf Scoter (Melanitta perspicillata) White-winged Scoter (Melanitta fusca) Common Goldeneye (Bucephala clangula) Barrow's Goldeneye (Bucephala islandica) Bufflehead (Bucephala albeola) Hooded Merganser (Lophodytes cucullatus) Common Merganser (Mergus merganser) Red-breasted Merganser (Mergus serrator) Ruddy Duck (Oxyura jamaicensis)
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) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.075 | 0.049 |
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".