Influence of genotype and geography on shell shape and morphometric trait variation among North Atlantic blue mussel (Mytilus spp.) populations
Bibliographic record
Abstract
The influence of geography and genotype on shell shape (outline) and trait (morphometric) variation among North Atlantic blue mussels and their hybrids has been examined. Shape differences among reference taxa (Mytilus trossulus, Mytilus edulis and Mytilus galloprovincialis) were consistent with an association between taxon-specific genes and shape genes. Newfoundland M. edulis × M. trossulus populations and northern Quebec M. trossulus populations exhibited an uncoupling of taxon-specific genes from shape genes, whereas Nova Scotia M. trossulus populations and SW England M. edulis × M. galloprovincialis populations exhibited an association between taxon-specific genes and shape genes. We found no evidence of a geographic effect (NE versus NW Atlantic) for shape variation, indicating that the genotype effect is stronger than any geographic effect at macrogeographic scales. Pronounced differences were observed in trait variability consistent with an association between taxon-specific genes and trait genes in European populations, and trait divergence of New York M. edulis from all European mussels. Trait variability in mussels from Newfoundland, Nova Scotia and northern Quebec indicated an uncoupling of taxon genes from trait genes, whereas trait variability in SW England M. edulis × M. galloprovincialis populations was consistent with background genotype, indicating a strong association between taxon genes and trait genes. A pronounced macrogeographic split (NE versus NW Atlantic) regardless of taxonomy was observed, indicating that geography exerts a greater influence than genotype on trait variation at the macrogeographic scale. This is consistent with pronounced within-taxon genetic divergence, indicative of different selection regimes or more likely of different evolutionary histories of mussels on either side of the North Atlantic.
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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 | 0.001 |
| 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".