Status and nesting distribution of Lesser Snow Geese, Chen caerulescens caerulescens, and Brant, Branta bernicla nigricans, on the western Arctic Coastal Plain, Alaska
Bibliographic record
Abstract
Status and nesting distribution of Lesser Snow Geese, Chen caerulescens caerulescens, and Brant, Branta bernicla nigricans, on the western Arctic Coastal Plain, Alaska.Canadian Field-Naturalist 114(3): 395-404.We describe the current status of nesting by Lesser Snow Geese (Chen caerulescens caerulescens) and Brant (Branta bernicla nigricans) on the western Arctic Coastal Plain of Alaska.We conducted aerial surveys along Alaska's Beaufort and Chukchi seacoasts in 1991-1998 to determine the current distribution and abundance of these two colonially nesting goose species and to monitor their status at selected colonies.Areas of optimal habitat were surveyed, so we doubt that any large colonies of either Snow Geese or Brant were missed.We obtained the first specific size and location information for two colonies of Snow Geese on the Kukpowruk and Ikpikpuk river deltas, which combined were occupied annually by a total of approximately 100 pairs.Snow Geese nested irregularly within the study area at 15 other locations that accounted for no more than 13 nests in any year.Museum records indicated that Snow Geese have nested near or at some of these sites since at least the 1930s.Brant were recorded nesting at 135 locations in the study area.The combined total number of nests (estimated by adding the highest recorded number of nests for all sites) was over 1070 (1-53 nests/location).The majority of these nests were located east of Barrow and within 10 km of the coast.Most nests were located on islets in shallow lakes and basin wetland complexes, but three colonies were located on deltaic islands.Historical information on Brant nesting locations in the region is limited.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".