Patterns and processes in amphibious fish: biomechanics and neural control of fish terrestrial locomotion
Bibliographic record
Abstract
Amphibiousness in fishes spans the actinopterygian tree from the earliest to the most recently derived species. The land environment requires locomotor force production different from that in water, and a diversity of locomotor modes have evolved across the actinopterygian tree. To compare locomotor mode between species, we mapped biomechanical traits on an established amphibious fish phylogeny. Although the diversity of fish that can move over land is large, we noted several patterns, including the rarity of morphological and locomotor specialization, correlations between body shape and locomotor mode, and an overall tendency for amphibious fish to be small. We suggest two idealized empirical metrics to consider when gauging terrestrial 'success' in fishes and discuss patterns of terrestriality in fishes considering biomechanical scaling, physical consequences of shape, and tissue plasticity. Finally, we suggest four ways in which neural control could change in response to a novel environment, highlighting the importance and challenges of deciphering when these control mechanisms are used. We aim to provide an overview of the diversity of successful amphibious locomotion strategies and suggest several frameworks that can guide the study of amphibious fish and their locomotion.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".