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Record W2925003071 · doi:10.1093/icb/icz013

The Ecomechanics of Gecko Adhesion: Natural Surface Topography, Evolution, and Biomimetics

2019· article· en· W2925003071 on OpenAlex
Timothy E. Higham, Anthony P. Russell, Peter H. Niewiarowski, Amber N. Wright, Thomas Speck

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueIntegrative and Comparative Biology · 2019
Typearticle
Languageen
FieldEngineering
TopicAdhesion, Friction, and Surface Interactions
Canadian institutionsUniversity of Calgary
FundersAlexander von Humboldt-StiftungNational Science Foundation
KeywordsGeckoBiomimeticsNatural (archaeology)EcologyNatural materialsHabitatMorphology (biology)NanotechnologyGeologyBiologyMaterials sciencePaleontologyPolymer science

Abstract

fetched live from OpenAlex

The study of gecko adhesion is necessarily interdisciplinary due to the hierarchical nature of the adhesive system and the complexity of interactions between the animals and their habitats. In nature, geckos move on a wide range of surfaces including soft sand dunes, trees, and rocks, but much of the research over the past two decades has focused on their adhesive performance on artificial surfaces. Exploring the complex interactions between geckos and their natural habitats will reveal aspects of the adhesive system that can be applied to biomimetic research, such as the factors that facilitate movement on dirty and rough surfaces with varying microtopography. Additionally, contrasting suites of constraints and topographies are found on rocks and plants, likely driving differences in locomotion and morphology. Our overarching goals are to bring to light several aspects of ecology that are important for gecko-habitat interactions, and to propose a framework for how they can inspire material scientists and functional ecologists. We also present new data on surface roughness and topography of a variety of surfaces, and adhesive performance of Phelsuma geckos on surfaces of varying roughness. We address the following key questions: (1) why and how should ecology be incorporated into the study of gecko adhesion? (2) What topographical features of rocks and plants likely drive adhesive performance? (3) How can ecological studies inform material science research? Recent advances in surface replication techniques that eliminate confounding factors among surface types facilitate the ability to address some of these questions. We pinpoint gaps in our understanding and identify key initiatives that should be adopted as we move forward. Most importantly, fine details of locomotor microhabitat use of both diurnal and nocturnal geckos are needed.

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.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.458
Threshold uncertainty score0.422

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)0.0000.000

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 head0.014
GPT teacher head0.252
Teacher spread0.239 · 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