Bibliographic record
Abstract
ABSTRACT. The numbers of brant (Branta bernicla) in the Pacific Flyway are relatively small compared to other populations of arctic geese and have declined from historic levels. Little information is available on brant from Banks Island, although the size of the island and its location in the western Canadian Arctic make it a potentially important nesting area for this species. In 1992–93, we documented the distribution of nesting brant on the southern half of Banks Island through aerial surveys and carried out ground studies at the colonies to document nesting chronology and reproductive parameters. Ten colonies were found in 1992 (n = 159 nests) and 42 colonies (including seven colonies that had been active in 1992) and five solitary nests were found in 1993 (n = 514 nests). Two-thirds (67%) of the nesting locations supported 10 or fewer nests. Most colonies (36 of 45) were located on small islands (mean = 248 m2) in inland lakes or large ponds, and the remaining colonies (n = 9) were located on the mainland near active snowy owl (Nyctea scandiaca) nests. In 1993, when June temperatures were milder and snow melted sooner than in 1992, mean date of clutch initiation was significantly earlier (12 June vs. 20 June in 1992; p < 0.001) and mean clutch size was significantly larger (3.8 vs. 3.5 in 1992; p = 0.02). An index of productivity for the 21 414 km2 area surveyed in both years was much higher in 1993 (1339 young) than in the very late spring of 1992 (347 young). The number of adult brant on the survey area was similar in both years, and the lower productivity in 1992 was due primarily to fewer pairs ’ nesting that year. Smaller clutch size and lower nesting success may also have lowered productivity in 1992, but their effects appeared to be secondary. No correlation was found between colony size and clutch size, mean number of goslings hatched, or the percentage of nests that proved successful.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.246 | 0.141 |
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".