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Record W2583805364 · doi:10.1098/rsos.160672

Earliest filter-feeding pterosaur from the Jurassic of China and ecological evolution of Pterodactyloidea

2017· article· en· W2583805364 on OpenAlexaff
Chang‐Fu Zhou, Ke‐Qin Gao, Hongyu Yi, Jinzhuang Xue, Quanguo Li, Richard C. Fox

Bibliographic record

VenueRoyal Society Open Science · 2017
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicPaleontology and Evolutionary Biology
Canadian institutionsUniversity of Alberta
FundersNational Natural Science Foundation of China
KeywordsCretaceousPaleontologyMesozoicBiologyVertebrateRange (aeronautics)Divergence (linguistics)EcologyStructural basin

Abstract

fetched live from OpenAlex

Pterosaurs were a unique clade of flying reptiles that were contemporaries of dinosaurs in Mesozoic ecosystems. The Pterodactyloidea as the most species-diverse group of pterosaurs dominated the sky during Cretaceous time, but earlier phases of their evolution remain poorly known. Here, we describe a 160 Ma filter-feeding pterosaur from western Liaoning, China, representing the geologically oldest record of the Ctenochasmatidae, a group of exclusive filter feeders characterized by an elongated snout and numerous fine teeth. The new pterosaur took the lead of a major ecological transition in pterosaur evolution from fish-catching to filter-feeding adaptation, prior to the Tithonian (145-152 Ma) diversification of the Ctenochasmatidae. Our research shows that the rise of ctenochasmatid pterosaurs was followed by the burst of eco-morphological divergence of other pterodactyloid clades, which involved a wide range of feeding adaptations that considerably altered the terrestrial ecosystems of the Cretaceous world.

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 score0.024
Threshold uncertainty score0.047

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.021
GPT teacher head0.254
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 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

Citations53
Published2017
Admission routes1
Has abstractyes

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