Spatial distribution and habitat selection of Barrow’s and Common goldeneyes wintering in the St. Lawrence marine system
Bibliographic record
Abstract
Our study addresses winter spatial distribution of Barrow’s Goldeneyes ( Bucephala islandica (Gmelin, 1789)) and Common Goldeneyes ( Bucephala clangula (L., 1758)) at the scale of the St. Lawrence marine system (estuary and northwestern gulf), eastern Canada. Our objectives were (i) to identify and compare the physical factors that control their distributions, (ii) to quantify the level of sympatry between the two species, and (iii) to compare their distribution patterns. We analyzed large-scale synoptic views of winter distribution of both goldeneye species obtained through helicopter-borne surveys. Habitat description was obtained through spatial analyses and remote sensing. Both species showed strong preference for the tidal zone and river mouths. A multiscale analysis showed a decreasing level of sympatry as spatial resolution was refined. The distribution of the Barrow’s Goldeneye was more clustered compared with that of the Common Goldeneye, and Barrow’s Goldeneye was repeatedly observed in the same few areas. A use-availability analysis identified the northern coast of the St. Lawrence estuary as the main wintering ground for Barrow’s Goldeneye in eastern North America.
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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 | 0.001 |
| 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) | 0.000 | 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".