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Record W4362507381 · doi:10.1126/science.abo7877

Theropod dinosaur facial reconstruction and the importance of soft tissues in paleobiology

2023· article· en· W4362507381 on OpenAlexaff
Thomas M. Cullen, Derek W. Larson, Mark P. Witton, Diane Scott, Tea Maho, Kirstin S. Brink, David C. Evans, Robert R. Reisz

Bibliographic record

VenueScience · 2023
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicPaleontology and Evolutionary Biology
Canadian institutionsRoyal Ontario MuseumUniversity of ManitobaRoyal British Columbia MuseumUniversity of TorontoCarleton University
Fundersnot available
KeywordsDentitionTheropodaBiologySkullExtant taxonEvolutionary biologyAnatomyPaleontologyTaxon

Abstract

fetched live from OpenAlex

Large theropod dinosaurs are often reconstructed with their marginal dentition exposed because of the enormous size of their teeth and their phylogenetic association to crocodylians. We tested this hypothesis using a multiproxy approach. Regressions of skull length and tooth size for a range of theropods and extant varanid lizards confirm that complete coverage of theropod dinosaur teeth with extraoral tissues (gingiva and labial scales) is both plausible and consistent with patterns observed in living ziphodont amniotes. Analyses of dental histology from crocodylians and theropod dinosaurs, including Tyrannosaurus rex , further indicate that the most likely condition was complete coverage of the marginal dentition with extraoral tissue when the mouth was closed. This changes our perceptions about the appearance and oral configuration of these iconic predators and has broad implications for our interpretations of other terrestrial animals with large teeth.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
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 head0.014
GPT teacher head0.235
Teacher spread0.221 · 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 designBench or experimental
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

Citations18
Published2023
Admission routes1
Has abstractyes

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