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Record W4410721523 · doi:10.3390/d17060375

Rediscovery of the Type Specimens of the Sarcopterygian Fishes Onychodus sigmoides and Onychodus hopkinsi from the Devonian of Ohio, USA

2025· article· en· W4410721523 on OpenAlexaboutno aff
Loren E. Babcock

Bibliographic record

VenueDiversity · 2025
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicPaleontology and Stratigraphy of Fossils
Canadian institutionsnot available
Fundersnot available
KeywordsDevonianType (biology)PaleontologyBiologyGeology

Abstract

fetched live from OpenAlex

John Strong Newberry described three species of the lobe-fin fish Onychodus (Osteichthyes, Sarcopterygii, Onychodontida) based on parasymphysial teeth, or tusks. Two species, Onychodus sigmoides Newberry, 1857 (type species of the genus) and Onychodus hopkinsi Newberry, 1857, were described from the “fish beds” in the Delaware Limestone (Middle Devonian, Eifelian) of Delaware, Ohio, USA; and one species, Onychodus ortoni Newberry, 1889, was described from the Ohio Shale, Huron Member (Upper Devonian, Famennian) of Perry Township, Franklin County, Ohio. In 1873, Newberry replaced the original species-group definition of O. hopkinsi with a definition based on teeth of different morphology from the West Falls Group (Upper Devonian, Frasnian) of Franklin, New York. Specimens of Newberry’s original Onychodus material, including the primary types, which were long assumed to be lost, have been rediscovered in a 19th-century collection. They show O. hopkinsi to be a junior synonym of O. sigmoides and clarify the species definition of O. sigmoides. Onychodus sigmoides, which is recognized from Middle Devonian strata of the Appalachian Basin in the United States and Canada, shows two end-member shapes of teeth on the parasymphysial whorl: procurved (arcuate) or nearly so proximally and recurved distally (anteriorly). Small teeth are commonly more slender than large teeth, which are robust. Parasymphysial teeth from the Upper Devonian of Ohio and New York are referred to O. ortoni.

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)0.000
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 score0.054
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

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

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 head0.015
GPT teacher head0.200
Teacher spread0.185 · 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

Citations3
Published2025
Admission routes1
Has abstractyes

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