Distribution and use of brood-rearing and moulting sites of the Atlantic population of Canada Geese (<em>Branta canadensis</em>) in Nunavik, Quebec
Bibliographic record
Abstract
The Atlantic population of Canada Geese (Branta canadensis) nests in the coastal lowlands of eastern Hudson Bay and southwestern Ungava Bay in Nunavik, Quebec. Although many aspects of the nesting ecology of this and other northern populations of Canada Geese have been studied and published, there is a paucity of information on the use of brood-rearing and moulting sites. Based on 18 years of band and recapture data from an ongoing banding program, this paper presents the distribution of brood-rearing and moulting sites and the use of these sites over time. Along Hudson Bay and Ungava Bay, the most important brood-rearing and moulting areas are the stretch of coastal lowlands between the Mariet River and Shallow Bay and between Rivière aux Feuilles and Virgin Lake, respectively. Of all adult geese captured during the banding program (n = 41 924), 7.5% (standard error [SE] 0.13%) were recaptures, that is, birds that had previously been caught and banded; annual recapture rates ranged from 5.1% to 11.4%. The mean and median distances between the site of first recapture and the original site of capture were 4.3 km (SE 0.22 km) and 1.5 km, respectively. Juveniles moved, on average, 5.4 km farther than adults and males moved 1.4 km farther than females. Among geese banded as juveniles, males moved twice as far as females: 11.5 km versus 5.7 km.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".