Shell shape, dysodont tooth morphology, and hinge-ligament thickness in the bay mussel <i>Mytilus trossulus</i> correlate with wave exposure
Bibliographic record
Abstract
We examined the shell morphology of the bay mussel Mytilus trossulus (Gould) at six locations with various levels of wave exposure in Barkley Sound on the west coast of Vancouver Island, British Columbia, Canada. Young adult M. trossulus (29-35 mm shell length) collected from wave-exposed sites displayed striking differences in shell morphology from M. trossulus from sheltered sites. Mytilus trossulus from wave-exposed habitats had a lower shell height / shell width ratio and a thicker shell; they also had higher, more robust dysodont teeth, as well as a thicker hinge ligament. Examination of juveniles (12-14 mm shell length) collected from a wave-exposed shore and a sheltered shore separated by only a few hundred metres displayed similar differences in shell morphology and ligament thickness. These observations suggest that wave exposure is the cause of the observed differences in shell morphology and ligament thickness in M. trossulus. This is the first report of a correlation between wave exposure and morphology of the dysodont teeth and ligament in a bivalve. We discuss potential selective pressures that may favor characteristics of wave-exposed shells, including the probability of dislodgment and misalignment of valves in high wave energy areas.
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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".