Development of an abundance estimate for the eastern Bering Sea stock of beluga1 whales (Delphinapterus leucas)
Bibliographic record
Abstract
The first dedicated aerial surveys for beluga whales in the Norton Sound/Yukon Delta region of Alaska were flown during May, June and September 1992. During May 1992 surveys, all of the survey area was covered with pack ice and only a few belugas were seen. In June 1992, many whales were seen in the region of Pastol Bay and the Yukon River Delta, with a few animals seen in eastern Norton Sound. In September 1992, whales were more dispersed and occurred both off the Yukon Delta and in coastal waters of northern Norton Sound. Based on those results, subsequent surveys were flown in June 1993–95 and 1999–2000. In all years except 1999 when there was extensive sea ice in the area, belugas were common off the Yukon Delta and in southern Norton Sound. In most years they were also seen in central Norton Sound. Density and abundance were estimated from the 2000 survey as it represented the most recent data and had the most complete and systematic coverage of the area. In June 2000, belugas were rare in the northern portion of Norton Sound, so the study area was reduced to central and southern Norton Sound and the Yukon Delta, which was divided into four strata by latitude. The density that was estimated with the model that received most Akaike Information Criterion support was 0.121 belugas km–2 and the number of belugas at the surface in the study area was estimated to be 3,497 (CV = 0.37). A generally accepted correction factor for availability of 2.0 was applied, resulting in an abundance estimate for the eastern Bering Sea beluga stock in June 2000 of 6,994 (95% confidence interval 3,162–15,472). This estimate is likely to be conservative. There are no previous abundance estimates for this region, so a population trend cannot be determined. The available evidence suggests that the current Alaska Native subsistence harvest from this stock is sustainable. Beluga consumption of prey populations is likely significant in the regional ecosystem and may have a particular impact on some stocks of Pacific salmon.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".