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Assessing the contribution of off‐fault deformation to slip‐rate estimates within the Taupo Rift, New Zealand, using 3‐D ground‐penetrating radar surveying and trenching

2009· article· en· W2023101377 on OpenAlexaff
Alastair McClymont, Pilar Villamor, Alan G. Green

Bibliographic record

VenueTerra Nova · 2009
Typearticle
Languageen
FieldEarth and Planetary Sciences
Topicearthquake and tectonic studies
Canadian institutionsUniversity of Calgary
FundersMarsden FundSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungEidgenössische Technische Hochschule ZürichRoyal Society Te ApārangiRoyal Society
KeywordsGeologyTrenchSeismologyGround-penetrating radarRiftGeodetic datumSlip (aerodynamics)Interferometric synthetic aperture radarFault (geology)RadarGeodesyTectonicsRemote sensingSynthetic aperture radar

Abstract

fetched live from OpenAlex

Abstract We demonstrate that conventional palaeoseismic trenching and mapping techniques that do not account for the effects of off‐fault deformation can significantly underestimate a fault’s slip rate. Using combined interpretations of 3‐D ground‐penetrating radar (GPR) and palaeoseismic trench data, we show that drag folding and hangingwall and footwall horizontal‐axis rotations have accommodated up to 41% of total extension across a normal fault within the Taupo Rift, New Zealand, over the past 24.6 ± 1.0 cal. ka BP. Our results may explain why geologically determined fault‐slip rates for the central and southern Taupo Rift are anomalously low when compared with geodetic estimates. We suggest that a combination of GPR surveying and palaeoseismic trenching may help resolve differences between geodetically and geologically determined strain rates observed across active extensional regimes worldwide.

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)0.001
metaresearch head score (Gemma)0.003
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 score0.130
Threshold uncertainty score0.258

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.047
GPT teacher head0.293
Teacher spread0.246 · 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

Citations22
Published2009
Admission routes1
Has abstractyes

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