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Structural characteristics of the patagium ofPtychozoon kuhli (Reptilia: Gekkonidae) in relation to parachuting locomotion

2001· article· en· W2021869331 on OpenAlexaff
Anthony P. Russell, Luke D. Dijkstra, G. Lawrence Powell

Bibliographic record

VenueJournal of Morphology · 2001
Typearticle
Languageen
FieldEnvironmental Science
TopicAmphibian and Reptile Biology
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsBiologyKeelGekkonidaeSquamataSnoutEnergeticsBody surfaceAnatomyAllometryZoologyEcologyGeometryGeologyMathematics

Abstract

fetched live from OpenAlex

Ptychozoon kuhli is known for its parachuting/gliding capabilities. In this contribution, we document the allometric scaling properties of its patagium, accessory flaps and folds, and its total body surface area and compare them to similar attributes of the agamine lizard Draco volans. Ptychozoon kuhli has passive patagia that lack skeletal support and muscular control. Patagial area in P. kuhli is smaller than that in D. volans for individuals of identical snout-vent length, but the accessory folds and flaps compensate for this shortfall and overall P. kuhli has equivalent total body surface area to D. volans for equally sized individuals. The structure of the patagium of Ptychozoon kuhli was investigated in terms of its scalation patterns and structural integrity, its relationship to the body wall and its mechanism of erection, and the distribution of mechanoreceptive sensilla across its surface. Scalation patterns and the internal architecture of the patagium indicate how its shape and form are maintained as it erects and becomes exposed to air flow. Its cross-sectional shape, together with that of the entire body indicates how it is able to behave as an airfoil. The distribution of sensilla across the patagial surface reflect positioning indicative of the monitoring of scale-to-scale contact on the dorsal surface, and possibly air pressure and flow on the ventral surface.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.078
Threshold uncertainty score0.650

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.013
GPT teacher head0.235
Teacher spread0.222 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations24
Published2001
Admission routes1
Has abstractyes

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