Nesting Biology of Lesser Canada Geese, <em>Branta canadensis parvipes</em>, along the Tanana River, Alaska
Bibliographic record
Abstract
Lesser Canada Geese (Branta canadensis parvipes) are widespread throughout interior regions of Alaska and Canada, yet there have been no published studies documenting basic aspects of their nesting biology. We conducted a study to determine reproductive parameters of Lesser Canada Geese nesting along the Tanana River near the city of Fairbanks, in interior Alaska. Fieldwork was conducted in May of 2003, and consisted of locating nests along the riparian corridor between Fairbanks and Northpole, Alaska. Nests were found on gravel islands and shore habitats along the Tanana River, and were most commonly observed among driftwood logs associated with patches of alder (Alnus spp.) and willow (Salix spp.). Peak of nest initiation was 3-8 May, with a range from 27 April to 20 May; renesting was likely. Clutches ranged in size from 2 to 7 eggs and averaged 4.6 eggs. There was a negative correlation between clutch size and date of nest initiation. Egg size (mean mass = 128 g) was similar to other medium-sized Canada Geese. A positive correlation between egg size and clutch size was likely related to female age. Nineteen of 28 nests (68%) were active when visited; nests located on islands with nesting Mew Gulls (Larus canus) were more likely to be active than nests located elsewhere. Evidence at nest sites implicated Bald Eagles (Haliaeetus leucocephalus) and Red Foxes (Vulpes vulpes) as nest predators.
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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 | 0.001 | 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".