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Record W2333038523 · doi:10.3997/2214-4609.201600019

How Big is Too Big? Assessing Seismic Hazard and Hydraulic Fracture-Induced Seismicity

2016· article· en· W2333038523 on OpenAlexaff
S. Bowman-Young, T. Urbancic, A. M. Baig, G. Viegas, Eric von Lunen, Jason Hendrick

Bibliographic record

VenueProceedings · 2016
Typearticle
Languageen
FieldComputer Science
TopicSeismology and Earthquake Studies
Canadian institutionsCanadian Apheresis Group
Fundersnot available
KeywordsInduced seismicityMagnitude (astronomy)SeismologyGeologySeismic hazardGround motionHydraulic fracturingHazardStress (linguistics)Hazard analysisTectonicsGeotechnical engineeringEngineeringPhysics

Abstract

fetched live from OpenAlex

Summary Regulations governing induced seismicity in certain jurisdictions favour having "traffic light" systems where recommended responses are based on the magnitude of the induced events. The lower stress drops of induced seismicity cause less shaking than equivalent-magnitude tectonic events with higher stress releases. Because of this observation, and since seismic hazard is actually quantified in terms of probabilities of exceeding ground motion thresholds (not magnitude), we recommend that observed shaking should be the pertinent quantity to use to regulate seismicity during injections, and show how this is done in terms of emperical ground motion prediction equations.

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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.924
Threshold uncertainty score0.712

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
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 head0.031
GPT teacher head0.244
Teacher spread0.214 · 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 designOther design
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

Citations0
Published2016
Admission routes1
Has abstractyes

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