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Dentes de terópodes da Formação Marília (Neomaastrichtiano) do sítio paleontológico de Peirópolis do estado de Minas Gerais, Brasil

2012· article· pt· W2106467558 on OpenAlexaff
Carlos Roberto dos Anjos Candeiro, Philip J. Currie, Lílian Paglarelli Bergqvist

Bibliographic record

VenueRevista Brasileira de Geociências · 2012
Typearticle
Languagept
FieldEarth and Planetary Sciences
TopicPaleontology and Evolutionary Biology
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsGeographyTaxonStructural basinPaleontologyArchaeologyHumanitiesBiologyArt

Abstract

fetched live from OpenAlex

Theropods comprise the most common vertebrate remains in the fossil assemblage from the Serra da Galga Member, Marília Formation (late Maastrichtian) in the Bauru Basin Peirópolis paleontological site (Uberaba Town, Minas Gerais State), in southeastern Brazil. In this study, cross-sectional outlines of the teeth and wrinkles on the surfaces of the crowns were used to group the teeth into nine morphological classes. The tooth cross-sections were drawn using a copper wire to contour the outlines of the most proximal portions of the tooth crowns. Other features were analyzed using a microscope. Within the nine morphological classes, morphotypes one and two can be assigned to the Abelisauridae, and morphotypes three to seven belong to the Carcharodontosauridae. This is the most abundant record of Abelisauridae in Minas Gerais State, Brazil. Morphotypes eight and nine were not identified because they do not have any diagnostic features of known Gondwanan or Laurasian taxa. The presence of Carcharodontosauridae teeth in the Member of Serra da Galga (late Maastrichtian) is the youngest record for this family.

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)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.097
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.025
GPT teacher head0.265
Teacher spread0.240 · 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 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

Citations18
Published2012
Admission routes1
Has abstractyes

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