Canada goose gosling survival of the Atlantic Flyway Resident Population
Bibliographic record
Abstract
ABSTRACT Gosling losses account for the majority of summer mortality for Canada geese (Branta canadensis), but survival at this stage can be difficult to estimate because of their small size, precocial behavior, and the land cover in which they live. Previous methods of measuring gosling survival often used individual markers, which can bias estimates when not accounting for total brood loss or emigration. We estimated gosling survival of Canada geese in the Atlantic Flyway Resident Population (AFRP) in New Jersey, USA, during 2009–2010 through use of marked parents and young to incorporate total and partial brood losses. The proportion of marked parents who lost their entire brood occurring during the first 3 weeks after hatch and prior to banding was 0.316. Gosling survival that accounted for partial brood loss was 0.461 ± 0.027 (SE), and was most influenced by nest density and the percent agriculture land use within 215 m of the nest site. The gosling survival estimate incorporating total and partial brood losses during this study was 0.315 ± 0.018. Acquiring current reproductive vital rates will assist in understanding the dynamics of recruitment as a function of population size. The above information, in combination with nest survival and annual survival estimates from band recovery and recapture analyses, has been used to inform a population model for Canada geese in the AFRP. © 2018 The Wildlife Society.
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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 | 0.000 | 0.000 |
| 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) | 0.001 | 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".