Pectoral fin morphology of batoid fishes (Chondrichthyes: Batoidea): Explaining phylogenetic variation with geometric morphometrics
Bibliographic record
Abstract
The diverse cartilaginous fish lineage, Batoidea (rays, skates, and allies), sister taxon to sharks, comprises a huge range of morphological diversity which to date remains unquantified and unexplained in terms of evolution or locomotor style. A recent molecular phylogeny has enabled us to confidently assess broadscale aspects of morphology across Batoidea. Geometric morphometrics quantifies the major aspects of shape variation, focusing on the enlarged pectoral fins which characterize batoids, to explore relationships between ancestry, locomotion and habitat. A database of 253 specimens, encompassing 60 of the 72 batoid genera, reveals that the majority of morphological variation across Batoidea is attributable to fin aspect-ratio and the chordwise location of fin apexes. Both aspect-ratio and apex location exhibit significant phylogenetic signal. Standardized independent linear contrast analysis reveals that fin aspect-ratio can predict locomotor style. This study provides the first evidence that low aspect-ratio fins are correlated with undulatory-style locomotion in batoids, whereas high aspect-ratio fins are correlated with oscillatory locomotion. We also show that it is phylogeny that determines locomotor style. In addition, body- and caudal fin-locomotors are shown to exhibit low aspect-ratio fins, whereas a pelagic lifestyle correlates with high aspect-ratio fins. These results emphasize the importance of phylogeny in determining batoid pectoral fin shape, however, interactions with other constraints, most notably locomotor style, are also highlighted as significant.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".