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Record W2125996645 · doi:10.1242/jeb.068080

A buckling region in locust hindlegs contains resilin and absorbs energy when jumping or kicking goes wrong

2012· article· en· W2125996645 on OpenAlexfundno aff
Timothy George Bayley, Gregory P. Sutton, Malcolm Burrows

Bibliographic record

VenueJournal of Experimental Biology · 2012
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCellular Mechanics and Interactions
Canadian institutionsnot available
FundersDalhousie UniversityCase Western Reserve University
KeywordsJumpingLocustTigerBiologyCommunicationEcologyComputer sciencePsychologyComputer securityPhysiology

Abstract

fetched live from OpenAlex

If a hindleg of a locust slips during jumping, or misses its target during kicking, energy generated by the two extensor tibiae muscles is no longer expended in raising the body or striking a target. How, then, is the energy in a jump (4100-4800 μJ) or kick (1700 μJ) dissipated? A specialised buckling region found in the proximal hind-tibia where the bending moment is high, but not present in the other legs, buckled and allowed the distal part of the tibia to extend. In jumps when a hindleg slipped, it bent by a mean of 23±14 deg at a velocity of 13.4±9.5 deg ms(-1); in kicks that failed to contact a target it bent by 32±16 deg at a velocity of 32.9±9.5 deg ms(-1). It also buckled 8.5±4.0 deg at a rate of 0.063±0.005 deg ms(-1) when the tibia was prevented from flexing fully about the femur in preparation for both these movements. By experimentally buckling this region through 40 deg at velocities of 0.001-0.65 deg ms(-1), we showed that one hindleg could store about 870 μJ on bending, of which 210 μJ was dissipated back to the leg on release. A band of blue fluorescence was revealed at the buckling region under UV illumination that had the two key signatures of the elastic protein resilin. A group of campaniform sensilla 300 μm proximal to the buckling region responded to imposed buckling movements. The features of the buckling region show that it can act as a shock absorber as proposed previously when jumping and kicking movements go wrong.

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 score0.031
Threshold uncertainty score0.391

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 head0.023
GPT teacher head0.297
Teacher spread0.274 · 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

Citations41
Published2012
Admission routes1
Has abstractyes

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