Availability to Steller sea lions (<i>Eumetopias jubatus</i>) of a seasonal prey resource: a prespawning aggregation of eulachon (<i>Thaleichthys pacificus</i>)
Bibliographic record
Abstract
The availability of seasonally abundant energy-rich prey can be a significant factor for the survival and reproductive success of predator populations. Large numbers of Steller sea lions (Eumetopias jubatus) were attracted to a prespawning aggregation of eulachon (Thaleichthys pacificus) in Berners Bay in southeast Alaska during AprilMay in 2002 and 2003. Sea lion abundance increased as eulachon gathered in Berners Bay, peaked as eulachon abundance peaked, and decreased as the eulachon moved up-river. As sea lion abundance increased in Berners Bay, sea lion abundance decreased at Benjamin Island, a sea lion haulout located 22 km away. The eulachon provided an abundant, energy-rich, predictable prey source for the Steller sea lions: (i) eulachon energy density was 9.70 ± 0.24 kJ·g1, much higher than that of any forage species reported in the North Pacific Ocean except northern lampfish (Stenobrachius leucopsarus); (ii) a large surplus of prey was available per sea lion while the eulachon aggregation was present; and (iii) the spawning run usually begins between late April and early May. The eulachon pulse may be critical to Steller sea lions during a period of high energetic demands.
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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 | 0.000 |
| 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".