Corrigendum: Closure violation in DNA-based mark-recapture estimation of grizzly bear populations
Bibliographic record
Abstract
It has been suggested that our paper “Closure violation in DNA-based mark–recapture estimation of grizzly bear populations” did not adequately cite the original data analysis from the Prophet River DNA mark–recapture project conducted by Poole et al. (2001). Poole et al. (2001), who designed and collected the DNA data for the Prophet River study, conducted their own mark–recapture analysis and reported other biological findings from the Prophet River dataset, which is detailed in the June 2001 issue of Wildlife Biology. The purpose of our paper was to demonstrate new techniques to explore closure violation rather than to report results from this specific study. Any lack of citation was an oversight and we suggest that readers see Poole et al. (2001) for more details on the Prophet River study.
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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 | 0.007 | 0.100 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.005 | 0.002 |
| Research integrity | 0.008 | 0.008 |
| Insufficient payload (model declined to judge) | 0.025 | 0.023 |
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".