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Record W4408406220 · doi:10.1144/sp556-2025-3

Sedimentary stasis in a Jurassic lagoonal delta system: the Lastres Formation of Asturias, northern Spain

2025· article· en· W4408406220 on OpenAlexaff
Anthony P. Shillito, Maximiliano Paz, Romain Gougeon, Luís A. Buatois, M. Gabriela Mángano, Laura Piñuela, José Carlos García-Ramos

Bibliographic record

VenueGeological Society London Special Publications · 2025
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeological formations and processes
Canadian institutionsUniversity of Saskatchewan
FundersInternational Association of Sedimentologists
KeywordsGeologyDeltaSedimentary rockPaleontologyGeomorphology

Abstract

fetched live from OpenAlex

The Jurassic Lastres Formation hosts a suite of well exposed deltaic facies, rendering it an ideal case study to understand the record of sedimentary stasis and true substrates within this broad depositional setting. With novel sedimentological and ichnological field data combined with existing literature, we discuss how durations of sedimentary stasis differ throughout the stratigraphy, ranging from years to centuries on floodplains, to hours to days in interdistributary bays, to instants within distributary channels. The likelihood of true substrates from any given environment being observed in the rock record increases with the recurrence frequency of stasis and preservation potential of the strata, and depends on a sufficiently long colonization window for signatures to be imparted. Intermediate durations lead to the best conditions for preservation of true substrates, as a relatively high recurrence frequency lines up with a sufficiently long colonization window and preservation potential. However, short stasis durations can provide informative snapshots of short-timescale events, and long stasis durations can provide broader palaeoenvironmental context that cannot otherwise be inferred.

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)0.001
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 score0.169
Threshold uncertainty score0.335

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.001
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 head0.014
GPT teacher head0.220
Teacher spread0.206 · 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

Citations4
Published2025
Admission routes1
Has abstractyes

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