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Record W2851025245 · doi:10.1029/2018jb015581

The<i>M</i>7 2016 Kumamoto, Japan, Earthquake: 3‐D Deformation Along the Fault and Within the Damage Zone Constrained From Differential Lidar Topography

2018· article· en· W2851025245 on OpenAlex
Chelsea Scott, J Ramón Arrowsmith, Edwin Nissen, L. J. Lajoie, Tadashi Maruyama, Tatsuro Chiba

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Geophysical Research Solid Earth · 2018
Typearticle
Languageen
FieldEarth and Planetary Sciences
Topicearthquake and tectonic studies
Canadian institutionsUniversity of Victoria
FundersSouthern California Earthquake CenterNational Science Foundation
KeywordsFault traceGeologySeismologyFault (geology)GeodesyDeformation (meteorology)Slip (aerodynamics)Echelon formationDisplacement (psychology)

Abstract

fetched live from OpenAlex

Abstract Three‐dimensional near‐fault coseismic deformation fields from high‐resolution differential topography provide new information on the behavior of the shallow fault zone in large surface‐rupturing earthquakes. Our work focuses on the 16 April 2016 M w 7.0 Kumamoto, Japan, earthquake, which ruptured ~40 km of the Futagawa‐Hinagu Fault Zone on Kyushu Island with an oblique strike‐slip mechanism and surface offset exceeding 2 m. Our differential lidar analysis constrains the structural style of strain accommodation along the primary fault trace and the surrounding damage zone. We show that 36 ± 29% and 62 ± 32% of the horizontal and vertical deformation, respectively, was accommodated off the principal fault trace. The horizontal strains of up to 0.03 suggest that the approximate elastic strain limit was exceeded over a ~250 m width in many locations along the rupture. The inelastic deformation of the fault volume produced the observed distributed deformation at the Earth's surface. We demonstrate a novel approach for calculating 3‐D displacement uncertainties, indicating errors of centimeters to a few decimeters for displacements computed over 50 m horizontal windows. Errors correlate with land cover and relief, with flatter agricultural land associated with the highest displacement uncertainty. These advances provide a framework for future analyses of shallow earthquake behavior using differential topography.

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.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.817
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.003
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.023
GPT teacher head0.281
Teacher spread0.259 · 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