Recruitment of mackerel icefish (<i>Champsocephalus gunnari</i>) at South Georgia indicated by predator diets and its relationship with sea surface temperature
Bibliographic record
Abstract
The South Georgia population of mackerel icefish (Champsocephalus gunnari) is exploited by both a fishery and predators, including gentoo penguins (Pygoscelis papua). Because considerable uncertainty surrounds recent estimates of stock size, there is a need to consider novel approaches that may give insight into the population dynamics of this species. We derive two indices of recruitment based on the occurrence of mackerel icefish in gentoo penguin diets, one of which is scaled by a survey estimate of the density of Antarctic krill (Euphausia superba), an alternative prey species for gentoo penguins. The closure of the fishery for much of the 1990s allowed the relationship between environmental conditions and recruitment to be studied without the confounding effects of fishing mortality. The recruitment indices were positively correlated with sea surface temperature with a lag time equal to the age of the fish. These results suggest strong links between mesoscale environmental processes and the smaller scale interaction between gentoo penguins and their mackerel icefish prey.
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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".