Fine-scale geographic interactions between Steller sea lion (<i>Eumetopias jubatus</i>) trends and local fisheries
Bibliographic record
Abstract
Fine-scale geographic interactions between Steller sea lion (Eumetopias jubatus) abundance trends and the abundance of local fisheries and commercial fishing efforts from Southeast Alaska to the Aleutian Islands were assessed. Census counts of Steller sea lions from 1976 to 2002 at 53 different trend sites and rookeries were grouped into 33 locales with similar population trends. Localized estimates of commercial groundfish biomass densities for walleye pollock (Theragra chalcogramma), Pacific cod (Gadus macrocephalus), arrowtooth flounder (Atheresthes stomias), and Atka mackerel (Pleurogrammus monopterygius) from 1983 to 2002 and localized estimates of commercial fishing effort from 1990 to 2002 were matched to the 33 locales. Generalized estimating equations methods found a negative relationship between Steller sea lion abundance trends and walleye pollock density (P < 0.10). However, the 4.8-fold change in walleye pollock density between 1984 and 2001 was estimated to change the rate of population change (λ) by only 0.029. The analysis estimated that elimination of all trawl fishing effort would increase λ by as little as 0.0056. Neither commercial groundfish abundance nor commercial fishing effort could explain the large historical declines in the rate of Steller sea lion population change observed.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".