Limb and digit orientation during vertical clinging in Bibron's gecko, <i>Chondrodactylus bibronii</i> (A. Smith, 1846) and its bearing on the adhesive capabilities of geckos
Bibliographic record
Abstract
Abstract Geckos with subdigital adhesive pads can scale smooth vertical surfaces in defiance of gravity. The deployment of the adhesive system is activated by the musculoskeletal system during active traverses of such surfaces, but adhesion on such substrata can also be achieved by passive means, with the body weight of the gecko applying tensile loading to the adhesive setae, maintaining prolonged, static contact with the surface. To investigate whether passively induced adhesion is employed by geckos holding station on smooth vertical surfaces, we investigated the magnitude of shear force generation for the manus and pes, and the positioning of the limb segments and digits in C hondrodactylus bibronii in freely selected resting postures (head‐up, head‐down and facing laterally to the left and right). Our results indicate that different subsets of digits occupy positions consistent with them being passively loaded in different body orientations. Limb segment and digit orientation are consistent within, and differ between, the resting postures, and relatively few of the 20 digits are positioned to take advantage of gravitationally induced loading in any posture. The pedal digits have greater adhesive potential than the manual ones and, more frequently, capitalize on passive loading than do manual digits. This is especially evident in the commonly adopted head‐down resting posture.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".