Exploratory Surveys of Migratory Birds Breeding in the Western and Central Canadian Arctic 2005–2011
Bibliographic record
Abstract
Abstract The Canadian Arctic and subarctic are the primary breeding areas of many species of North American water and land birds. Because of the remote location and the logistical difficulties of working there, wildlife biologists have not systematically surveyed most important areas for wildlife, nor have they surveyed these areas very frequently. During the summers of 2005–2011, various Joint Ventures, and U.S., Canadian, and state wildlife agencies and other partners funded exploratory fixed-wing aircraft surveys of migratory birds (excluding passerines and shorebirds) in important habitats in Canada's western and central Arctic. Our objectives were to provide access to the complete survey dataset (all bird and mammal observations and associated location data) and summarize information on several species. Thus, we produced maps of average relative density and estimates of abundance in the survey area for cackling geese Branta hutchinsii, greater white-fronted geese Anser albifrons, tundra swans Cygnus columbianus, king eiders Somateria spectabilis, long-tailed ducks Clangula hyemalis, white-winged Melanitta fusca and surf Melanitta perspicillatas scoters, and yellow-billed Gavia adamsii, red-throated Gavia stellata, and Pacific Gavia pacifica loons. We reviewed previous survey efforts in the area and, where possible, compared them with our results.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".