Breeding Ecology of Sympatric Greater and Lesser Scaup (<i>Aythya marila</i> and <i>Aythya affinis</i>) in the Subarctic Northwest Territories
Bibliographic record
Abstract
We studied the breeding ecology of greater and lesser scaup on islands of the North Arm of Great Slave Lake, Northwest Territories, and on the nearby mainland during 1990-98. The occurrence of nests of both species on the North Arm islands was determined primarily by the distribution of nesting gulls and terns and secondarily by habitat features. Nest parasitism was frequent on the islands, but not on the mainland. Average clutch size was 8.99 ± 0.12 (n = 169) for greater scaup and 9.20 ± 0.17 (n = 93) for lesser scaup on the North Arm, and 8.71 ± 0.18 (n = 55) for lesser scaup on the mainland. No greater scaup nests were found on the mainland. Apparent nest success on the islands was higher (greater scaup 75%, n = 271; lesser scaup 77%, n = 158) than on the mainland (lesser scaup 37%, n = 59). Apparent egg success was 63% (n = 1485) for greater scaup and 67% (n = 934) for lesser scaup on the islands, and 40% (n = 435) for lesser scaup on the mainland. Hatchability of eggs was 98% (n = 556) for greater scaup and 94% (n = 416) for lesser scaup on islands, and 98% (n = 435) for lesser scaup on the mainland. Our findings, when compared to those of previous studies, do not indicate that either clutch size or egg hatchability has declined in recent years. Therefore, it seems unlikely that broad changes in these reproductive parameters are responsible for local or continental declines in lesser scaup populations. However, nest success on our mainland study area may have been too low to maintain the local population.
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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 | 0.001 | 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".