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Record W2051339983 · doi:10.1139/cjz-2013-0219

Challenges and advances in the study of pterosaur flight

2014· article· en· W2051339983 on OpenAlexvenueno aff
Kevin M. Middleton, Lauren T. English

Bibliographic record

VenueCanadian Journal of Zoology · 2014
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicPaleontology and Evolutionary Biology
Canadian institutionsnot available
FundersUniversity of North Carolina at Chapel Hill
KeywordsBiologyExtant taxonPaleontologyBird flightEvolutionary biologyRange (aeronautics)ZoologyWing

Abstract

fetched live from OpenAlex

Pterosaurs have fascinated scientists and nonscientists alike for over 200 years, as one of the three known clades of vertebrates to have evolved flapping flight. The smallest pterosaurs were comparable in size to the smallest extant birds and bats, but the largest pterosaurs were vastly larger than any extant flier. This immense size range, coupled with poor preservation and adaptations for flight unknown in extant vertebrates, have made interpretations of pterosaur flight problematic and often contentious. Here we review the anatomical, evolutionary, and phylogenetic history of pterosaurs, as well as the views, perspectives, and biases regarding their interpretation. In recent years, three areas of pterosaur biology have faced challenges and made advances: structure of the wing membrane, function of the pteroid, body size and mass estimates, as well as flight mechanics and aerodynamics. Comparative anatomical and fossil study, simulated bone loading, and aerodynamic modeling have all proved successful in furthering our understanding of pterosaur flight. We agree with previous authors that pterosaurs should be studied as pterosaurs, a diverse but phylogenetically, anatomically, and mechanically constrained clade that can offer new insights into the diversity of vertebrate 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 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)0.014
metaresearch head score (Gemma)0.014
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.014
Threshold uncertainty score0.073

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.014
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0010.007
Scholarly communication0.0030.008
Open science0.0020.003
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0030.001

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 head0.019
GPT teacher head0.215
Teacher spread0.196 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations13
Published2014
Admission routes1
Has abstractyes

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