Comparative Brain Morphology of the Greenland and Pacific Sleeper Sharks and its Functional Implications
Bibliographic record
Abstract
In cartilaginous fishes, variability in the size of the brain and its major regions is often associated with primary habitat and/or specific behavior patterns, which may allow for predictions on the relative importance of different sensory modalities. The Greenland (Somniosus microcephalus) and Pacific sleeper (S. pacificus) sharks are the only non-lamnid shark species found in the Arctic and are among the longest living vertebrates ever described. Despite a presumed visual impairment caused by the regular presence of parasitic ocular lesions, coupled with the fact that locomotory muscle power is often depressed at cold temperatures, these sharks remain capable of capturing active prey, including pinnipeds. Using magnetic resonance imaging (MRI), brain organization of S. microcephalus and S. pacificus was assessed in the context of up to 117 other cartilaginous fish species, using phylogenetic comparative techniques. Notably, the region of the brain responsible for motor control (cerebellum) is small and lacking foliation, a characteristic not yet described for any other large-bodied (>3 m) shark. Further, the development of the optic tectum is relatively reduced, while olfactory brain regions are among the largest of any shark species described to date, suggestive of an olfactory-mediated rather than a visually-mediated lifestyle.
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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) | 0.001 | 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".