Revisiting the classification of squamate adhesive setae: historical, morphological and functional perspectives
Bibliographic record
Abstract
Research on gecko-based adhesion has become a truly interdisciplinary endeavour, encompassing many disciplines within the natural and physical sciences. Gecko adhesion occurs by the induction of van der Waals intermolecular (and possibly other) forces between substrata and integumentary filaments (setae) terminating in at least one spatulate tip. Gecko setae have increasingly been idealized as structures with uniform dimensions and a particular branching pattern. Approaches to developing synthetic simulacra have largely adopted such an idealized form as a foundational template. Observations of entire setal fields of geckos and anoles have, however, revealed extensive, predictable variation in setal form. Some filaments of these fields do not fulfil the morphological criteria that characterize setae and, problematically, recent authors have applied the term 'seta' to structurally simpler and likely non-adhesively competent fibrils. Herein we briefly review the history of the definition of squamate setae and propose a standardized classificatory scheme for epidermal outgrowths based on a combination of whole animal performance and morphology. Our review is by no means comprehensive of the literature regarding the form, function, and development of the adhesive setae of squamates and we do not address significant advances that have been made in many areas (e.g. cell biology of setae) that are largely tangential to their classification and identification. We contend that those who aspire to simulate the form and function of squamate setae will benefit from a fuller appreciation of the diversity of these structures, thereby assisting in the identification of features most relevant to their objectives.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.008 | 0.005 |
| Science and technology studies | 0.002 | 0.008 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".