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Record W4307812068 · doi:10.1038/s41598-022-22791-z

A reservoir induced earthquake swarm in the Central Highlands of Sri Lanka

2022· article· en· W4307812068 on OpenAlexaff
Pasan Herath, Januka Attanayake, Kalpna Gahalaut

Bibliographic record

VenueScientific Reports · 2022
Typearticle
Languageen
FieldEarth and Planetary Sciences
Topicearthquake and tectonic studies
Canadian institutionsUniversity of Ottawa
FundersFaculty of Science, University of MelbourneUniversity of Peradeniya
KeywordsSeismologyGeologyInduced seismicityEarthquake swarmSeismic hazardRemotely triggered earthquakesSwarm behaviour

Abstract

fetched live from OpenAlex

< 3) felt earthquakes occurred between 29 August 2020 and 05 December 2020 around the Victoria Reservoir in the central highlands of Sri Lanka that clearly exceeded the established national background seismic rate. Using seismic waveform template-matching and a newly developed single-station earthquake location method based on travel-time back-projection, we detected an additional co-located 23 microseismic events, of which 18 occurred within the same period as the felt events. This hitherto undetected seismic swarm defines a seismogenic zone beneath the western flank of the reservoir between 1.5 and 3 km depths. The reservoir-induced peak stresses, resolved on E-W striking faults, predicted from the poroelastic theory that include both drained and undrained crustal responses are ~ 15 kPa in an area overlapping the seismogenic zone, which, together with the physical and spatio-temporal characteristics of the seismic swarm, establish a causal link between reservoir-induced stresses and the earthquake swarm with implications to seismic hazard. This is the first record of induced seismicity in Sri Lanka. The newly developed efficient computational workflows with minimal operational costs described in our study provide a blueprint for monitoring reservoir-induced seismicity in developing countries with severe resource limitations.

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)0.000
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 score0.022
Threshold uncertainty score0.043

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.026
GPT teacher head0.229
Teacher spread0.203 · 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

Citations16
Published2022
Admission routes1
Has abstractyes

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