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Record W4361271493 · doi:10.1144/sp537-2022-222

Re-evaluating metamorphism in the southern Natal Province, South Africa

2023· article· en· W4361271493 on OpenAlexaff
Eleanore Blereau, Christopher J. Spencer

Bibliographic record

VenueGeological Society London Special Publications · 2023
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeological and Geochemical Analysis
Canadian institutionsQueen's University
FundersBrigham Young University
KeywordsMetamorphismTerraneGeologyGranuliteMetamorphic rockGeochemistryMetamorphic faciesPetrologyFaciesGeomorphologyPaleontologyTectonics

Abstract

fetched live from OpenAlex

Abstract The metamorphic conditions of the Natal Metamorphic Province (NMP) have been the focus of previous studies to assist with Rodinia reconstructions but there are limited constraints on the age of metamorphism. We use a combination of modern techniques to provide new constraints on the conditions and timing of metamorphism in the two southernmost terranes: the Mzumbe and Margate. Metamorphism reached granulite facies, 780–834°C at 3.9–7.8 kbar in the Mzumbe Terrane and 850–892°C at 5.7–6.1 kbar in the Margate Terrane. The new pressure and temperature constraints are supportive of isobaric cooling in the Margate Terrane as previously proposed. Peak metamorphism of the two terranes is shown to have occurred c. 40 myr apart, which contrasts strongly with previous assumptions of coeval metamorphism. While the age of peak metamorphism of the Margate Terrane (1032.7 ± 4.7 Ma) coincides with the tectonism and magmatism associated with the emplacement of the Oribi Gorge Suite ( c. 1050–1030 Ma), the age of metamorphism of the Mzumbe Terrane (987.4 ± 8.1 Ma) occurs c. 30–40 myr after tectonism is previously thought to have finished. We propose that models of advective cooling during transcurrent shearing can explain the metamorphic conditions and timing of the NMP.

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)0.002
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 score0.193
Threshold uncertainty score0.384

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.003
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.052
GPT teacher head0.249
Teacher spread0.197 · 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

Citations2
Published2023
Admission routes1
Has abstractyes

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