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Record W6948341564 · doi:10.5061/dryad.5gs6p

Data from: Palaeoecological inferences for the fossil Australian snakes Yurlunggur and Wonambi (Serpentes, Madtsoiidae)

2017· dataset· en· W6948341564 on OpenAlexaff

Bibliographic record

VenueData Archiving and Networked Services (DANS) · 2017
Typedataset
Languageen
FieldImmunology and Microbiology
TopicToxoplasma gondii Research Studies
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsPaleoecologyPostcraniaEndocastMorphometricsTheropodaFossil RecordTaxonTaphonomy

Abstract

fetched live from OpenAlex

Madtsoiids are among the most basal snakes, with a fossil record dating back to the Upper Cretaceous (Cenomanian). Most representatives went extinct by the end of the Eocene, but some survived in Australia until the late Cenozoic. Yurlunggur and Wonambi are two of these late forms, and also the best-known madtsoiids to date. A better understanding of the anatomy and palaeoecology of these taxa may shed light on the evolution and extinction of this poorly known group of snakes and on early snake evolution in general. A digital endocast of the inner ear of Yurlunggur was compared to those of 81 species of snakes and lizards with known ecological preferences using three-dimensional geometric morphometrics. The inner ear of Yurlunggur most closely resembles both that of certain semiaquatic snakes and that of some semifossorial snakes. Other cranial and postcranial features of this snake support the semifossorial interpretation. While the digital endocast of the inner ear of Wonambi is too incomplete to be included in a geometric morphometrics study, its preserved morphology is very different from Yurlunggur and suggests a more generalist ecology. Osteology, palaeoclimatic data, and the palaeobiogeographic distribution of these two snakes are all consistent with these inferred ecological differences.

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 categoriesMeta-epidemiology (narrow), Science and technology studies, Open science
Consensus categoriesOpen science
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.078
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0020.002
Scholarly communication0.0010.000
Open science0.0090.012
Research integrity0.0010.001
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 head0.093
GPT teacher head0.355
Teacher spread0.262 · 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; both teacher heads agree on what is shown here.

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
Published2017
Admission routes1
Has abstractyes

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