MétaCan
Menu
Back to cohort
Record W4411021561 · doi:10.3390/geosciences15060210

Milankovitch- and Millennial-Scale Sequences in the Late Piacenzian to Early Gelasian Shelf Succession of the Crotone Basin, Southern Italy

2025· article· en· W4411021561 on OpenAlexaff
Massimo Zecchin, Mauro Caffau, Octavian Catuneanu

Bibliographic record

VenueGeosciences · 2025
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeological formations and processes
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsEcological successionMilankovitch cyclesGeologyPaleontologyStructural basinOceanographyGlacial periodEcology

Abstract

fetched live from OpenAlex

Integrated facies and micropaleontological analyses of the late Piacenzian to early Gelasian, middle shelf to lower shoreface succession of the Strongoli area, southern Italy, reveal a hierarchy of transgressive–regressive sequences. In particular, higher rank sequences up to ca. 40 m thick, composed of transgressive systems tract, highstand systems tracts and falling stage plus lowstand systems tracts, are composed of 10–11 lower rank sequences 2.5–4 m thick. Some micropaleontological parameters were defined: distal/proximal (D/P; ratio between distal and proximal benthic foraminifera); fragmentation (Fr; percentage of fragmentation of benthic foraminifera); P/B (ratio between planktonic and benthic foraminifera); abundance (total count of individuals); diversity (sum of the recognized species). Among these parameters, the D/P and Fr are suitable, if used in conjunction, to recognize uncertainty intervals containing the maximum flooding surface (between the D/P maxima and Fr minima) and the maximum regressive surface (between D/P minima and Fr maxima). Moreover, combining these parameters with the sedimentological evidence, it is possible to recognize transgressive and regressive trends of different hierarchical ranks. The present results are an example illustrating how an integration of different types of data allows the recognition of high-frequency sequences in shelf settings associated with minor shoreline shifts, which would otherwise have been unrecognized on the basis of only one kind of data. The present integrated approach, therefore, provides a way to improve the resolution of sequence stratigraphic analyses.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.008
GPT teacher head0.217
Teacher spread0.209 · 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.

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

Citations1
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueGeosciencesSame topicGeological formations and processesFrench-language works237,207