Apparent survival, natal philopatry, and recruitment of Barrow’s goldeneyes (Bucephala islandica) in the Cariboo–Chilcotin region of British Columbia, Canada
Bibliographic record
Abstract
We used capture–resight data to evaluate apparent survival, natal philopatry, and recruitment of Barrow’s goldeneyes ( Bucephala islandica (Gmelin, 1789)) in British Columbia, Canada. Median ages of first pairing and first breeding for females were 2 years and 3 years, respectively. The Cormack–Jolly–Seber model that best fit our data indicated that apparent survival rates (Φ) differed according to sex, year, and age class at marking. Estimates were similar for after-hatch-year (AHY) females (0.62) and AHY males (0.58), which was consistent with predictions. However, contrary to predictions, apparent survival rates of hatch-year (HY) females (0.68) were similar to those of AHY females and significantly higher than those of HY males (0.35). We interpret this difference as being primarily related to higher dispersal probabilities by HY males. Also evident was a negative correlation between apparent survival rate during the 1st year after capture for HY birds and their subsequent apparent survival rates, which suggests that probability of dispersal increased after these birds reached reproductive maturity and began to compete for breeding territories. We interpret this as evidence for density-dependent control of access to limited resources such as nest cavities.
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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 | 0.001 |
| 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".