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Record W2088110146 · doi:10.1371/journal.pone.0094518

The Oldest Caseid Synapsid from the Late Pennsylvanian of Kansas, and the Evolution of Herbivory in Terrestrial Vertebrates

2014· article· en· W2088110146 on OpenAlexaff
Robert R. Reisz, Jörg Fröbisch

Bibliographic record

VenuePLoS ONE · 2014
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicEvolution and Paleontology Studies
Canadian institutionsUniversity of Toronto
FundersBundesministerium für Bildung und ForschungAlexander von Humboldt-Stiftung
KeywordsHerbivorePennsylvanianTerrestrial ecosystemBiologyVertebrateCarboniferousEcologyPaleozoicEcosystemCladeTerrestrial plantPaleontologyPhylogenetics

Abstract

fetched live from OpenAlex

The origin and early evolution of amniotes (fully terrestrial vertebrates) led to major changes in the structure and hierarchy of terrestrial ecosystems. The first appearance of herbivores played a pivotal role in this transformation. After an early bifurcation into Reptilia and Synapsida (including mammals) 315 Ma, synapsids dominated Paleozoic terrestrial vertebrate communities, with the herbivorous caseids representing the largest vertebrates on land. Eocasea martini gen. et sp. nov., a small carnivorous caseid from the Late Carboniferous, extends significantly the fossil record of Caseidae, and permits the first clade-based study of the origin and initial evolution of herbivory in terrestrial tetrapods. Our results demonstrate for the first time that large caseid herbivores evolved from small, non-herbivorous caseids. This pattern is mirrored by three other clades, documenting multiple, independent, but temporally staggered origins of herbivory and increase in body size among early terrestrial tetrapods, leading to patterns consistent with modern terrestrial ecosystem.

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 score0.029
Threshold uncertainty score0.057

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 communication0.0010.001
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 head0.019
GPT teacher head0.183
Teacher spread0.164 · 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

Citations122
Published2014
Admission routes1
Has abstractyes

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Same venuePLoS ONESame topicEvolution and Paleontology StudiesFrench-language works237,207