Band reporting probabilities of mallards, American black ducks, and wood ducks in eastern North America
Bibliographic record
Abstract
ABSTRACT Estimates of band reporting probabilities are used for managing North American waterfowl to convert band recovery probabilities into harvest probabilities, which are used to set harvest regulations. Band reporting probability is the probability that someone who has shot and retrieved a banded bird will report the band. This probability can vary relative to a number of factors, particularly the inscription on the band and the ease with which it can be reported. Other factors, such as geographic reporting region, and species and sex of the bird may also play a role. We tested whether reporting probabilities of wood ducks (Aix sponsa) and American black ducks (black ducks; Anas rubripes) differed from those of mallards (Anas platyrhynchos) and whether band reporting varied geographically or by the sex of the banded bird. In the analysis of spatially comparable wood duck and mallard data, a band reporting probability of 0.73 (95% CI = 0.67–0.78) was appropriate for use across species, sex, and reporting region within the United States. In the black duck–mallard comparison, the band reporting probability of black ducks in Eastern Canada (0.50, 95% CI = 0.44–0.57) was lower than in the Eastern United States (0.73, 95% CI = 0.62–0.83). These estimates reflected an increase in overall band reporting probability following the addition of a toll‐free telephone number to band inscriptions. Lower reporting in Eastern Canada may be because of cultural, linguistic, or logistical barriers. © 2013 The Wildlife Society.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".