Major hotspots detected along the Scotia Ridge in autumn for southern right whales <i>Eubalaena australis</i>, Antarctic fur seals <i>Arctocephalus gazella</i> and Antarctic prions <i>Pachyptila desolata</i>
Bibliographic record
Abstract
We investigated the role of hydrological features, such as water masses, fronts, eddies, and sea ice, in affecting the distribution of upper trophic level species in the Scotia Sea region during autumn. On board RV Polarstern, we performed 365 30-min strip transects recording seabirds and marine mammals along the North Scotia Ridge and the South Sandwich Trench in March—April 2013. Among the 7 identified cetacean species recorded, the humpback whale Megaptera novaeangliae was the most abundant baleen whale (40 individuals), and noteworthy were sightings of six southern right whales Eubalaena australis. Pinnipeds (3 species, 1650 individuals) were dominated by Antarctic fur seal Arctocephalus gazella (99%), and seabirds (36 species, 18900 individuals) by Antarctic prion Pachyptila desolata (~50%). The distribution of these top predators was highly patchy with the majority of observations concentrated in a few counts. This heterogeneity is likely a result of prey availability, and we discuss how hydrological features may have caused the patchiness.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".