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Record W4400974552 · doi:10.1126/science.adj9587

Fault size–dependent fracture energy explains multiscale seismicity and cascading earthquakes

2024· article· en· W4400974552 on OpenAlexaff
Alice‐Agnes Gabriel, Dmitry Garagash, Kadek Hendrawan Palgunadi, P. Martín

Bibliographic record

VenueScience · 2024
Typearticle
Languageen
FieldEarth and Planetary Sciences
Topicearthquake and tectonic studies
Canadian institutionsDalhousie University
Fundersnot available
KeywordsInduced seismicitySeismologyGeologyFault (geology)Seismic energy

Abstract

fetched live from OpenAlex

Earthquakes vary in size over many orders of magnitude, often rupturing in complex multifault and multievent sequences. Despite the large number of observed earthquakes, the scaling of the earthquake energy budget remains enigmatic. We propose that fundamentally different fracture processes govern small and large earthquakes. We combined seismological observations with physics-based earthquake models, finding that both dynamic weakening and restrengthening effects are non-negligible in the energy budget of small earthquakes. We established a linear scaling relationship between fracture energy and fault size and a break in scaling with slip. We applied this scaling using supercomputing and unveiled large dynamic rupture earthquake cascades involving >700 multiscale fractures within a fault damage zone. We provide a simple explanation for seismicity across all scales with implications for comprehending earthquake genesis and multifault rupture cascades.

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 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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.813
Threshold uncertainty score0.660

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0000.000
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 head0.010
GPT teacher head0.227
Teacher spread0.216 · 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 teacher head, 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

Citations55
Published2024
Admission routes1
Has abstractyes

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