MétaCan
Menu
Back to cohort
Record W4313449260 · doi:10.1130/g50551.1

Origin of the Sierras Pampeanas, Argentina: Flat-slab subduction and inherited structures

2022· article· en· W4313449260 on OpenAlexaff
Xiaowen Liu, Claire A. Currie

Bibliographic record

VenueGeology · 2022
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeological and Geochemical Analysis
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsGeologySubductionSlabSlab windowRidgeDeformation (meteorology)SeismologyFlatteningConvergent boundaryOceanic crustPaleontologyTectonics

Abstract

fetched live from OpenAlex

Abstract The Sierras Pampeanas (27°–33°S) in South America are characterized by basementcored uplifts and shortening that occurs >500 km from the nearest convergent margin. The deformation correlates spatially and temporally with an area of flat-slab subduction of the Nazca plate in the last 10 m.y. We use two-dimensional thermal-mechanical models to study the dynamics of Pampean flat-slab subduction and the origin of the Sierras Pampeanas. Models examine a geological time from ca. 12 Ma to present day, during which time the Juan Fernández Ridge subducted beneath South America. Models show that the buoyant ridge triggers slab flattening, resulting in regional continental compression through end loading at the plate margin. Deformation in the continental interior depends on the inherited structure of the continent, where surface uplifts and shortening are concentrated at preexisting weak zones. The inboard migration of deformation is controlled by surface topography caused by the buoyant ridge rather than basal shear from the growing flat slab. Deformation occurs prior to the passage of the ridge and is inhibited when the ridge is beneath the region owing to dynamic uplift.

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 score0.064
Threshold uncertainty score0.127

Distilled classifier scores by category (both heads)

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 communication0.0010.000
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 head0.013
GPT teacher head0.191
Teacher spread0.179 · 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

Citations8
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueGeologySame topicGeological and Geochemical AnalysisFrench-language works237,207