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Record W4313404147 · doi:10.29169/1927-5129.2022.18.13

Geodynamics of Alpine Belt and Caribbean Region: Plate - Tectonics and Plume - Tectonics

2022· article· en· W4313404147 on OpenAlexvenueno aff
Valentina Svalova

Bibliographic record

VenueJournal of Basic & Applied Sciences · 2022
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeological and Geochemical Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsDiapirGeologyAsthenosphereMantle (geology)GeodynamicsLithospherePlate tectonicsMantle convectionMantle plumeEarth scienceGeophysicsPaleontologyTectonics

Abstract

fetched live from OpenAlex

The origin and evolution of geological structures reflect lithosphere-asthenosphere interaction in the process of lithospheric plate movement. Mantle diapirs contribute significantly to the sedimentary basins formation in Alpine belt and Caribbean region. Mantle diapirs are the result of density inversion in the asthenosphere–lithosphere system in the periods of tectonomagmatic activations. Increasing heat flow and mantle diapirs on the phone of convergence of Africa and Eurasia in Alpine belt and North and South Americas in Caribbean region produce intercontinental seas in the Cenozoic. The analytical solution of the problem give possibility to find the critical parameters connecting the mantle flow dynamics with surface relief evolution. In Alpine belt, the mantle diapirs form new basins at the final stage of Africa–Eurasia collision in the Cenozoic. In the Caribbean region, great mantle diapir separates the North and South Americas in the Mesozoic, and then the diapir is the source for different smaller diapirs during the convergence of these continents in the Cenozoic. The Gulf of Mexico and Pre-Caspian Depression are connected with mantle diapirs upwelling and have common geological-geophysical features as very rich oil-gas and salt bearing structures. Geodynamics of Alpine belt and the Caribbean region is determined by plume - tectonics on background of plate - tectonics in these regions.

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 score0.199
Threshold uncertainty score0.656

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 studies0.0000.001
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 head0.012
GPT teacher head0.188
Teacher spread0.177 · 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

Citations0
Published2022
Admission routes1
Has abstractyes

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