Harbor porpoise (<i>Phocoena phocoena</i>) recovery in the inland waters of Washington: estimates of density and abundance from aerial surveys, 2013–2015
Bibliographic record
Abstract
The harbor porpoise (Phocoena phocoena (L., 1758)) used to be common in Puget Sound, Washington, but virtually disappeared from these waters by the 1970s. We conducted systematic aerial line-transect surveys (17 237 km total effort) for harbor porpoises, with the goal of estimating density and abundance in the inland waters of Washington State. Surveys in Puget Sound occurred throughout the year from 2013 to 2015, and in the Strait of Juan de Fuca and the San Juan Islands (and some adjacent Canadian waters) in April 2015. We used a high-wing, twin-engine Partenavia airplane and four observers (one on each side of the plane, one looking through a belly port, and one recording data). A total of 1063 harbor porpoise groups were sighted. Density and abundance were estimated using conventional distance sampling methods. Analyses were limited to 447 harbor porpoise groups observed during 5708 km of effort during good sighting conditions suitable for line-transect analysis. Harbor porpoises occurred in all regions of the study area, with highest densities around the San Juan Islands and in northern Puget Sound. Overall, estimated abundance for the Washington Inland Waters stock was 11 233 porpoises (CV = 37%, 95% CI = 9 616 – 13 120). This project clearly demonstrated that harbor porpoises have reoccupied waters of Puget Sound and are present there in all seasons. However, the specific reasons for their initial decline and subsequent recovery remain uncertain.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".