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Record W6929594266 · doi:10.5061/dryad.jsxksn0ng

Data from: Enlargement of sternum traits facilitated the evolution of powered flight in birds

2025· dataset· en· W6929594266 on OpenAlexaff

Bibliographic record

VenueOpen MIND · 2025
Typedataset
Languageen
FieldAgricultural and Biological Sciences
TopicPostharvest Quality and Shelf Life Management
Canadian institutionsRoyal Ontario MuseumUniversity of Toronto
Fundersnot available
KeywordsSternumKeelSternaWingBird flightAppendageBasal (medicine)

Abstract

fetched live from OpenAlex

An enlarged sternum with a prominent keel is a central feature of the flight apparatus of modern birds. However, sterna of near-bird dinosaurs (Pennaraptora) and early avialans are either significantly different from those of living birds or absent altogether, raising questions on how specialized sternal structures evolved in birds and how they are related to function. This remains poorly understood due to the fragmentary nature of the fossil record, and the challenges in inferring form and function from crushed fossils. We employ ancestral character estimations to trace sternal trait acquisition through the bird stem group, and multivariate phylogenetic regressions to analyze relationships between sternum morphology, body mass, and flight capabilities. We find that sternum evolution was episodic: basal members of Pennaraptora had proportionally small sterna, which became larger and more craniocaudally elongated in Avialae. This enlargement precedes the appearance of a midline ridge, a possible precursor of the sternal keel, in Pygostylia. Sternum size increased again in crownward Ornithuromorpha, alongside a fully formed sternal keel and enlarged caudal projections, both critical areas of flight muscle attachment. Sternal experimentation in relation to flight characteristics occurs multiple times throughout Pennaraptora, including within Paraves and Enantiornithes, indicating that powered flight may have evolved multiple times before proliferating in crown-group birds.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.053
Threshold uncertainty score0.998

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 science0.0030.002
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.107
GPT teacher head0.327
Teacher spread0.219 · 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.

Study designNot applicable
Domainnot available
GenreDataset

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

Citations1
Published2025
Admission routes1
Has abstractyes

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