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Record W4417187006 · doi:10.1098/rsif.2025.0416

Muscle power output reflects elevated viscosity in the propulsion system of flying miniature wasps

2025· article· en· W4417187006 on OpenAlexaff
Amir Sarig, Thomas Engels, Fritz‐Olaf Lehmann, Gal Ribak

Bibliographic record

VenueJournal of The Royal Society Interface · 2025
Typearticle
Languageen
FieldEngineering
TopicBiomimetic flight and propulsion mechanisms
Canadian institutionsCanadian Nautical Research Society
FundersGrand Équipement National De Calcul IntensifDeutsche Forschungsgemeinschaft
KeywordsWingDragFlappingPropulsionLift (data mining)Insect flightAerodynamicsKinematicsStall (fluid mechanics)Lift-to-drag ratio

Abstract

fetched live from OpenAlex

Air viscosity compromises aerodynamic lift production in the smallest flying insects, leading to increased flight costs. Miniature insects thus utilize both lift and drag for weight support, but the exact energetic costs of wing flapping at low Reynolds number are widely unexplored. We estimated flight power in the miniature wasp Eretmocerus mundus. Wing kinematics was three-dimensionally reconstructed using high-speed video and computational fluid dynamics simulated air flows, aerodynamic forces and moments. We found an asymmetrical crescent-shaped wingtip trajectory with the upstroke posterior to the downstroke path. This fore-aft distance increases with increasing horizontal flight velocity, maintaining the wing's backwards rowing motion needed for drag-based propulsion. Although the wing's lift-to-drag ratio is below unity, lift is the predominant force responsible for weight support and forward thrust. Elevated drag leads to mass-specific mechanical power output of 118 ± 9.0 W kg-1 flight muscle, which exceeds most power estimates reported for other insects, birds and bats. The elevated energetic costs for flight may have fostered the development of bristled wings in miniature insects. Altogether, our study of wingbeat control and flight costs in a miniature insect extends the scope of flight mechanisms to the smallest flying animals, revealing limits of miniaturization during the evolution of flight.

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)0.001
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 score0.113
Threshold uncertainty score0.298

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0010.000
Research integrity0.0000.001
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 head0.008
GPT teacher head0.231
Teacher spread0.223 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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