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Record W2038233387 · doi:10.1242/jeb.077917

AHEAD OF THE GAME: HOW KNOCKED INSECTS STICK

2013· article· en· W2038233387 on OpenAlexaff
Katie E. Marshall

Bibliographic record

VenueJournal of Experimental Biology · 2013
Typearticle
Languageen
FieldEngineering
TopicAdhesion, Friction, and Surface Interactions
Canadian institutionsWestern University
Fundersnot available
KeywordsCommunicationAdvertisingZoologyBiologyPsychologyBusiness

Abstract

fetched live from OpenAlex

While watching an insect skitter straight up a wall may cause jitters in the squeamish, this remarkable feat fascinates scientists interested in animal biomechanics. Because insects have immensely sticky feet capable of clinging to smooth vertical surfaces, to be able to run they must be able to rapidly attach and detach their feet. They do this by rapidly inflating and deflating the adhesive pads on the bottoms of their feet using a claw flexor muscle running through their legs. But it turns out the adhesive pads can still inflate and deflate rapidly even without flexing the muscle – a useful skill for arboreal insects when sudden wind gusts could send an inadequately sticky insect flying.To take a better look at this ability, Thomas Endlein from the University of Glasgow, UK, and Walter Federle from the University of Cambridge, UK, placed unsuspecting weaver ants and stick insects into a booby-trapped upside-down Petri dish. The lid of the dish had a cutout containing a glass coverslip, which was glued to a cantilevered beam. Whenever an insect stepped on the coverslip, it triggered a bolt that knocked the side of the beam, rapidly jolting the insect. A high-speed camera mounted above allowed the researchers to record and then later measure the size of the adhesive pad on the order of milliseconds.To their surprise, the researchers found that insects were able to massively increase the contact area of their sticky pads to the coverslip within the first 2 ms after a jolt. Neuromuscular responses in insects usually take 5–15 ms, suggesting that the increase in adhesion was not related to triggering the claw muscle. Instead, the researchers propose that the insects utilize a ‘preflex’ – a mechanical response that can occur passively without the control of the insect's nervous system.The researchers also observed an increase in the contact area 10–15 ms after the jolt, which they believe represented the action of the claw muscle. In addition, the researchers found that the more aligned an ant's foot was to the direction of the jolt, the greater the increase in contact area, while stick insect feet responded more evenly to jolts from different directions. The researchers suggested this might be due to differing mechanisms of the preflex in each species.Running is a complicated balancing act for animals that climb vertically: too sticky and they cannot move, not sticky enough and they fall. But in an uncertain world filled with sudden gusts of wind and inconvenient raindrops, having a little preflex insurance can make all the difference.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.323

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 head0.013
GPT teacher head0.248
Teacher spread0.235 · 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 designBench or experimental
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

Citations1
Published2013
Admission routes1
Has abstractyes

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