MétaCan
Menu
Back to cohort
Record W2762323557 · doi:10.1038/s41467-017-01223-x

The biomechanical origin of extreme wing allometry in hummingbirds

2017· article· en· W2762323557 on OpenAlexaff
Dimitri A. Skandalis, Paolo S. Segre, Joseph W. Bahlman, Derrick J. E. Groom, Kenneth C. Welch, Christopher C. Witt, Jimmy A. McGuire, Robert Dudley, David Lentink, Douglas L. Altshuler

Bibliographic record

VenueNature Communications · 2017
Typearticle
Languageen
FieldEngineering
TopicBiomimetic flight and propulsion mechanisms
Canadian institutionsThe Scarborough HospitalUniversity of TorontoUniversity of British Columbia
FundersAir Force Office of Scientific ResearchNational Science Foundation
KeywordsWingAllometryBiologyIntraspecific competitionHumAdaptation (eye)ZoologyBody weightEvolutionary biologyEcologyPhysics

Abstract

fetched live from OpenAlex

Flying animals of different masses vary widely in body proportions, but the functional implications of this variation are often unclear. We address this ambiguity by developing an integrative allometric approach, which we apply here to hummingbirds to examine how the physical environment, wing morphology and stroke kinematics have contributed to the evolution of their highly specialised flight. Surprisingly, hummingbirds maintain constant wing velocity despite an order of magnitude variation in body weight; increased weight is supported solely through disproportionate increases in wing area. Conversely, wing velocity increases with body weight within species, compensating for lower relative wing area in larger individuals. By comparing inter- and intraspecific allometries, we find that the extreme wing area allometry of hummingbirds is likely an adaptation to maintain constant burst flight capacity and induced power requirements with increasing weight. Selection for relatively large wings simultaneously maximises aerial performance and minimises flight costs, which are essential elements of humming bird life history.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.051
GPT teacher head0.310
Teacher spread0.260 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations47
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueNature CommunicationsSame topicBiomimetic flight and propulsion mechanismsFrench-language works237,207