Review Of Criteria For Index Sites For Monitoring Seal Abundance And Trends: Application To Southern New England
Bibliographic record
Abstract
No abstracts are to be cited without prior reference to the author.New England populations of harbour seal and grey seal have increased and expanded their range since passage of the U.S. Marine Mammal Protection Act, (1972). In autumn there is an influx of harbour seals from Maine and the Canadian Maritimes into southern New England,(SNE; Massachusetts to western Long Island, New York), that generally departs the region by mid-May. Grey seal numbers increase during the autumn as well and peak during the winter breeding season (January/February) and then decrease by late May. Intermittent autumn to spring monitoring surveys have been conducted in SNE since winter 1998/1999. However, the high cost of aerial surveys has made it difficult to maintain coast-wide seal monitoring surveys in SNE. Therefore, we have evaluated criteria used in other regions to monitor seals to determine their applicability and practicality to SNE. Criteria considered include: operational (i.e., survey design); ecological (i.e., life history, site fidelity); and extrinsic (i.e., human disturbance) denote sites that are subject to disturbance factors. Based on this review we developed a two-stage survey that should provide a suitable index of SNE seal populations. Stage I requires monthly (October - May) aerial surveys of major SNE sites, particularly grey seal pupping sites. In Stage II a comprehensive census of all haul-out sites would be conducted over a 3-5 day window (mid-March). Stage II corresponds to the period of peak harbour seal counts, and would provide a reference point for the Stage I surveys. We believe the spatial and temporal range of the survey will provide sufficient data to adequately monitor abundance trends in SNE region.
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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 | 0.021 | 0.067 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.019 | 0.021 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.003 |
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".