Between a rock and a soft place: microtopography of the locomotor substrate and the morphology of the setal fields of <scp>N</scp>amibian day geckos (<scp>G</scp>ekkota: <scp>G</scp>ekkonidae: <i><scp>R</scp>hoptropus</i>)
Bibliographic record
Abstract
Abstract Many species of gekkotans possess adhesive subdigital pads that allow them to adhere to, and move on, a wide variety of surfaces. The natural surfaces exploited by these lizards may be rough, undulant and unpredictable and therefore likely provide only limited, patchy areas for adhesive contact. Here, we examine the microtopography of rock surfaces used by seven species of R hoptropus and compare this to several rough and smooth artificial surfaces employed in previous studies of gekkotan adhesion. These data are considered in relation to the form, configuration, compliance and functional morphology of the setal fields of these species. Our results demonstrate that natural rock surfaces are rough and unpredictable at the scale of the setal arrays, with equal amounts of variation existing within and between the various types of rock surfaces examined. Such surfaces differ from smooth and rough artificial surfaces in the proportion of surface area available for attachment and the relative predictability of surface undulance. Generally, setal field characteristics of individual species are not relatable to specific substrates, but instead are configured to allow for sufficient attachment to a wide variety of unpredictable surfaces. Our findings provide insight into the evolution and microanatomy of the adhesive system of gekkotan lizards and its adaptive relationship to topographically unpredictable surfaces.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".