Seasonal residency, activity space, and use of deep-water channels by Greenland sharks (<i>Somniosus microcephalus</i>) in an Arctic fjord system
Bibliographic record
Abstract
As Arctic ecosystems become increasingly vulnerable to climate- and human-induced stressors, effective marine management will rely on the characterization of fish movements. Over a six-year study period, the movements of 65 Greenland sharks (Somniosus microcephalus) (41 males, 24 females; mean LT = 2.48 ± 0.50 m) were monitored using static acoustic telemetry. Shark presence in a typical deep-water fjord was restricted to the summer open-water period. Residency duration varied based on age class (juvenile, n = 17; subadult, n = 48); however, activity space size and extent were comparable. A quarter of tagged sharks (n = 16) returned to the system in subsequent years after tagging, with individuals redetected for a maximum of 4 years. Movements between coastal and offshore waters occurred primarily via a deep-water channel with sharks detected along the channel banks. These multiyear data depict how a potentially vulnerable Arctic predator utilizes a deep-water fjord in the context of the regional development of community inshore and offshore commercial fisheries.
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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 | 0.001 | 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) | 0.000 | 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".