Are survival rates for northern spotted owls biased?
Bibliographic record
Abstract
The northern spotted owl (Strix occidentalis caurina (Merriam, 1898)) is listed as threatened in both Canada and the United States. As part of a 1998–2004 study of habitat usage, we attached radio tags to 197 northern spotted owls. Owls that died or emigrated from the study areas could be identified with high certainty. The long-term data we obtained enabled us to estimate survivorship using multiple statistical methods. Using a pooled data set, we estimated annual survivorship at 0.927. Using a year-by-year analysis, we obtained some variation in survival by year, but the same overall mean. Using a staggered-entry cohort approach, we obtained an estimate of 0.934. Mean annual survival estimated by program MARK was 0.927. These estimates are outside the confidence intervals of prior studies that used capture–recapture methods. Capture–recapture methods are based on the assumption that birds remain within a demographic study area, but our data suggest that owls may disperse or remain undetected within a study area often enough that capture–recapture methods may overestimate mortality. Our results imply that the true finite population growth rate, λ, may be higher than estimated in prior studies that used capture–recapture methods.
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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 | 0.004 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".