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Record W2604430144 · doi:10.1130/ges01373.1

Defining shear zone boundaries using fabric intensity gradients: An example from the east-central Nepal Himalaya

2017· article· en· W2604430144 on OpenAlexafffund
Kyle P. Larson, John M. Cottle, Graham Lederer, S.M. Rai

Bibliographic record

VenueGeosphere · 2017
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeological and Geochemical Analysis
Canadian institutionsOkanagan University CollegeUniversity of British Columbia, Okanagan CampusUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of CanadaNational Science Foundation
KeywordsGeologyShear zoneShear (geology)Main Central ThrustPetrographyGeochronologyThrustZirconQuartzKinematicsGeochemistryStructural geologyPetrologyGeometrySeismologyPaleontologyMetamorphic rockTectonics

Abstract

fetched live from OpenAlex

Uranium-lead (U-Pb) zircon geochronology, whole-rock geochemistry, and petrographic observations indicate that specimens from a suite of variably deformed granite and orthogneiss from the Okhaldungha region of east-central Nepal share a common origin. Microtextural characterization and quartz crystallographic fabric preferred orientation analyses of these same specimens outline a strain gradient that marks the location of a shear zone boundary. The location of this boundary, at the base of the orthogneiss, coincides with one of the interpreted locations of the Main Central thrust, though it cannot be uniquely identified as such. This study provides the first steps toward empirical constraints on the location and geometry of thrust structures in the region, helping to clarify the complex local kinematic framework. These methods not only help in assessing orogenic models of the Himalaya, but may also be applied to investigating other orogenic systems where the potential location of shear structures is contested.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.034
Threshold uncertainty score0.068

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
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 head0.035
GPT teacher head0.215
Teacher spread0.180 · 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

Citations32
Published2017
Admission routes2
Has abstractyes

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