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Functional morphology of neck musculature in the Tyrannosauridae (Dinosauria, Theropoda) as determined via a hierarchical inferential approach

2007· article· en· W1835408683 on OpenAlexaff
Eric Snively, Anthony P. Russell

Bibliographic record

VenueZoological Journal of the Linnean Society · 2007
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicPaleontology and Evolutionary Biology
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsBiologyTheropodaAnatomyKinematicsFacial musclesEvolutionary biologyPaleontology

Abstract

fetched live from OpenAlex

With multiple well-preserved specimens, tyrannosaurid dinosaurs are ideal subjects for exploring the role of the neck for feeding in an extinct amniote clade. Detailed exploration of the morphology of avian and crocodilian neck muscles grounds phylogenetic inference of musculature of tyrannosaurids. Introduced methods of kinematic and physiological inference explicate action and function of tyrannosaurid neck muscles, and the explicit method of extant behavioural interpolation (EBI) allows inference of generalized behaviours. Anteriorly originating craniocervical muscles of tyrannosaurids, and insertions of the neck dorsiflexor m. transversospinalis cervicis, were similar to those of birds, while the major respective head dorsiflexor and lateroflexor, m. transversospinalis capitis and m. longissimus capitis superficialis, resembled their homologues in crocodilians. Because the proposed inferential methods are cumulative and emphasize mutual falsification, behavioural effects of muscle function become immediately testable rather than assumed. Kinematic inference of muscle moment topology, and bracketed and unipolar inference of muscle activity, facilitate EBI of rapid gaze shifts, lateral and sagittal strikes, inertial feeding, and tearing of flesh by specific permutational actions of tyrannosaurid neck muscles. Several examples of EBI are tested further through biomechanical considerations.

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)0.002
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 score0.006
Threshold uncertainty score0.555

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.017
GPT teacher head0.225
Teacher spread0.208 · 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

Citations73
Published2007
Admission routes1
Has abstractyes

Explore more

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