Segmentations in fins enable large morphing amplitudes combined with high flexural stiffness for fish-inspired robotic materials
Bibliographic record
Abstract
Fish fins do not contain muscles, yet fish can change their shape with high precision and speed to produce large and complex hydrodynamic forces-a combination of high morphing efficiency and high flexural stiffness that is rare in modern morphing and robotic materials. These "flexo-morphing" capabilities are rare in modern morphing and robotic materials. The thin rays that stiffen the fins and transmit actuation include mineral segments, a prominent feature whose mechanics and function are not fully understood. Here, we use mechanical modeling and mechanical testing on 3D-printed ray models to show that the function of the segmentation is to provide combinations of high flexural stiffness and high morphing amplitude that are critical to the performance of the fins and would not be possible with rays made of a continuous material. Fish fin-inspired designs that combine very soft materials and very stiff segments can provide robotic materials with large morphing amplitudes and strong grasping forces.
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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 | 0.000 | 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) | 0.002 | 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".