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Record W2981663850 · doi:10.1126/sciadv.aaw6670

Range of motion in the avian wing is strongly associated with flight behavior and body mass

2019· article· en· W2981663850 on OpenAlexaff
Vikram B. Baliga, Ildikò Szabó, Douglas L. Altshuler

Bibliographic record

VenueScience Advances · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicAvian ecology and behavior
Canadian institutionsRoyal British Columbia MuseumUniversity of British Columbia
FundersAir Force Office of Scientific Research
KeywordsWingRange (aeronautics)Motion (physics)BiologyAeronauticsAerospace engineeringPhysicsClassical mechanicsEngineering

Abstract

fetched live from OpenAlex

Avian wing shape is highly variable across species but only coarsely associated with flight behavior, performance, and body mass. An underexplored but potentially explanatory feature is the ability of birds to actively change wing shape to meet aerodynamic and behavioral demands. Across 61 species, we found strong associations with flight behavior and mass for range of motion traits but not wing shape and strikingly different associations for different aspects of motion capability. Further, static morphology exhibits high phylogenetic signal, whereas range of motion shows greater evolutionary lability. These results suggest a new framework for understanding the evolution of avian flight: Rather than wing morphology, it is range of motion, an emergent property of morphology, that is predominantly reshaped as flight strategy and body size evolve.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score0.308

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 studies0.0000.001
Scholarly communication0.0000.001
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 head0.007
GPT teacher head0.242
Teacher spread0.234 · 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 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

Citations65
Published2019
Admission routes1
Has abstractyes

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