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Record W1847171330 · doi:10.1029/2006tc001992

Metamorphism, transient mid‐crustal rheology, strain localization and the exhumation of high‐grade metamorphic rocks

2008· article· en· W1847171330 on OpenAlexaff
Wesley G. Groome, Peter O. Koons, Scott E. Johnson

Bibliographic record

VenueTectonics · 2008
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeological and Geochemical Analysis
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsGeologyMetamorphic rockMetamorphismShear zoneCrustStrain rateSeismologyPetrologyDeformation (meteorology)KinematicsShear (geology)TectonicsGeochemistry

Abstract

fetched live from OpenAlex

We present a series of three‐dimensional numerical models investigating the effects of metamorphic strengthening and weakening on the geodynamic evolution of convergent orogens that are constrained by observations from an exposed mid‐crustal section in the New England Appalachians. The natural mid‐crustal section records evidence for spatially and temporally variable mid‐crustal strength as a function of metamorphic grade during prograde polymetamorphism. Our models address changes in strain rate partitioning and topographic uplift as a function of strengthening/weakening in the middle crust, as well as the resultant changes in deformation kinematics and potential exhumation patterns of high‐grade metamorphic rock. Results suggest that strengthening leads to strain rate partitioning around the zone and suppressed topographic uplift rates whereas weakening leads to strain rate partitioning into the zone and enhanced topographic uplift rates. Deformation kinematics recorded in the orogen are also affected by strengthening/weakening, with complete reversals in shear sense occurring as a function of strengthening/weakening without changes in plate boundary kinematics.

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 score0.039
Threshold uncertainty score0.077

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.000
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 head0.016
GPT teacher head0.187
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

Citations18
Published2008
Admission routes1
Has abstractyes

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