Stock assessment of Pacific harbour seals (Phoca vitulina richardii) in Canada in 2019
Bibliographic record
Abstract
Standardized aerial surveys were conducted between 2015-2019 to assess the abundance of Harbour Seals in British Columbia (BC). Approximately 90% of the entire coastline was covered using fixed-wing aircraft to count seals hauled-out on land during specific low-tide windows. Five years were required to survey all regions of BC, and thus, this assessment represents a compilation of surveys. Thirty-two satellite transmitters were deployed on adult and juvenile seals between 2019-2021 to estimate the proportion hauled-out, and to calculate a correction factor for animals at-sea and not present at the time of the surveys. An estimate of 78.5% of the seals were hauled-out during the survey period. This marks a substantial change from the last derivation from the early 1990’s, when 62% of the seals were hauled-out. After applying the most recent correction factor, adjusting estimates for survey coverage, and summing regional abundance estimates in the year surveyed, 84,500 (95% CI 81,160 to 87,970) harbour seals were estimated in BC in 2015 – 2019. Projecting all regional trends to 2019 yielded a total estimate of 86,000 (95% CI 74,750 to 98,990) harbour seals in BC waters. Potential Biological Removal (PBR) estimated at 4,895 seals in 2019. While regional PBR allocations were estimated, they were deemed problematic as they may lead to local depletions. Correcting past surveys for uncovered areas resulted in an updated estimate for 2003-2008 of 112,400 (95% CI 108,000-117,000) seals, which is similar to the initial estimate of 105,000 seals (95% CI of 90,900-118,900). Given the uncertainty in the regional estimates, the stock in 2015-2019 is considered either stable or in slight decline relative to the 2003-2008 assessment. Abundance, density and trends varied regionally.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".