Muscle power output reflects elevated viscosity in the propulsion system of flying miniature wasps
Bibliographic record
Abstract
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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".