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Record W7103157247 · doi:10.1080/08912963.2025.2580968

Comments on Fernández et al. (2025): clarifying a misinterpretation of the Itaboraí Basin estimated age

2025· article· en· W7103157247 on OpenAlexaff

Bibliographic record

VenueHistorical Biology · 2025
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeological and Tectonic Studies in Latin America
Canadian institutionsCanadian Historical Association
FundersFundação Carlos Chagas Filho de Amparo à Pesquisa do Estado do Rio de JaneiroConselho Nacional de Desenvolvimento Científico e Tecnológico
KeywordsStructural basinContext (archaeology)Identification (biology)Population

Abstract

fetched live from OpenAlex

Fernández et al. (2025) favoured the previous chronological hypothesis of an early Eocene age for the Itaboraí Basin, Brazil, based on the isotopic dating of the ankaramite (~54.89 Ma) and a single fossil vertebrate (~55 Ma), but overlooked that this locality may range from late Palaeocene to early Eocene in age. Fernández et al. (2025) statement suggested that Bergqvist et al. (2024) proposed a unique late Palaeocene age for the Itaboraian SALMA; however, this likely stems from a misunderstanding of their proposal. The age estimation made by Woodburne et al. (2014) for the Itaboraian SALMA (53–50 Ma, contemporaneous to the Early Eocene Climatic Optimum) cannot be applied to the entire basin, as this locality preserved multiple fossiliferous strata (Itaboraí I/MCT-2 fissure and Itaboraí II/Itaboraian SALMA [MN and MCT-1; type faunas]). Additionally, the dates provided by the isotopic dating are unfit to confidently establish the age of the Itaboraí faunas, as their topographic and stratigraphic relationships within the basin remain undefined and cannot be further investigated because the limestone has been almost completely exploited. Bergqvist et al. (2024) considered only the fauna from the MCT-2 fissure as latest Palaeocene-earliest Eocene in age.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.763
Threshold uncertainty score1.000

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.034
GPT teacher head0.294
Teacher spread0.260 · 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.

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

Citations1
Published2025
Admission routes1
Has abstractyes

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