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Record W3107373700 · doi:10.1038/s43247-020-00052-z

Weak orogenic lithosphere guides the pattern of plume-triggered supercontinent break-up

2020· article· en· W3107373700 on OpenAlexaff
Zhuo Dang, Nan Zhang, Zheng‐Xiang Li, Chuan Huang, Christopher J. Spencer, Yebo Liu

Bibliographic record

VenueCommunications Earth & Environment · 2020
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeological and Geochemical Analysis
Canadian institutionsQueen's University
FundersNorthwest Fisheries Science CenterNational Natural Science Foundation of China-Yunnan Joint FundRecruitment Program of Global ExpertsPeking UniversityNational Natural Science Foundation of ChinaCurtin University of Technology
KeywordsGeologySupercontinentCratonRiftGondwanaLithosphereEarth sciencePaleontologyPlate tectonicsMantle plumeTectonicsTectonophysicsGeophysics

Abstract

fetched live from OpenAlex

Abstract The importance of nonrigid geological features (such as orogens) inside tectonic plates on Earth’s dynamic evolution lacks thorough investigation. In particular, the influence of continent-spanning orogens on (super)continental break-up remains unclear. Here we reconstruct global orogens and model their controlling effects on Pangea break-up. We show that while loci of Pangea break-up are linked to mantle plumes, development of continental rifts is guided by orogens. Rifting at Central Atlantic is driven by the modelled plume responsible for the Central Atlantic Magmatic Province (CAMP) within Pangea-forming orogens. South Atlantic rifting is controlled by necking between Pangea- and Gondwana-forming orogens with the assistance of plume-induced lithospheric weakening. Without CAMP-induced weakening, South Atlantic rifting fails between the West African and Amazonian cratons, but occurs between the West African and Saharan cratons instead. Our modeling on Pangea break-up is able to recreate present-day continental geometry through the combined effect of orogens and plume center-locations.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.017
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.028
GPT teacher head0.199
Teacher spread0.171 · 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

Citations48
Published2020
Admission routes1
Has abstractyes

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