Abundance and PBR Estimates for High Arctic Walrus Management Stocks
Bibliographic record
Abstract
The High Arctic Atlantic walrus (Odobenus rosmarus rosmarus) population in the eastern Canadian Arctic comprises three management stocks: Penny Strait-Lancaster Sound (PS-LS), West Jones Sound (WJS), and Baffin Bay (BB). Photographic aerial surveys of haulout sites and adjoining coastline were flown during August 2022 to update stock abundances last estimated in 2009. The areas that were surveyed included most of the known distributions of the PS-LS and WJS stocks and focused on the summer core-use area of the BB stock. Two surveys of both the PS-LS (August 13-16 and 24-27) and WJS (August 17-18 and August 22) stocks were completed, while the summer core-use area of the BB stock was surveyed three times (August 7, 16, and 26). Abundance estimates from the first survey replicates of each stock were used as the basis for scientific advice due to uncertainty regarding walrus movements between subsequent surveys. Abundance estimates accounted for animals at sea during the survey using the average proportion of time hauled-out (P = 0.3) and correlated walrus haulout behaviour. First survey abundance estimates were 887 (95% confidence interval [CI] = 475–1,653) for the PS-LS stock; 1,157 (95% CI = 618–2,166) for the WJS stock, and 847 (95% CI = 254* – 3,286) for the BB stock. Potential Biological Removal (PBR) estimates based on the first surveys of each stock are 6.8 walruses for the PS-LS stock, 8.8 for the WJS stock, and 4.7 for the BB stock. PBR estimates were calculated using a recovery factor (RF) of 0.25. PBR estimates are heavily dependent on the selected RF value and updated PBR estimates may differ from previous estimates largely due to this term in the calculation. Reported Canadian hunts from each of the three High Arctic management stocks are generally lower than PBR estimates. However, the winter hunt of walruses in Greenland exceeds the PBR estimate for the shared BB stock.
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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 | 0.002 | 0.003 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".