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Record W1972253275 · doi:10.1190/1.3353726

It's a matter of size: Magnitude and moment estimates for microseismic data

2010· article· en· W1972253275 on OpenAlexaff
Julie Shemeta, Paul F. Anderson

Bibliographic record

VenueThe Leading Edge · 2010
Typearticle
Languageen
FieldEarth and Planetary Sciences
Topicearthquake and tectonic studies
Canadian institutionsApache (Canada)
Fundersnot available
KeywordsMicroseismGeophoneMagnitude (astronomy)BoreholeGeologySeismologyHydraulic fracturingFracture (geology)Seismic momentMoment (physics)Geotechnical engineeringPhysics

Abstract

fetched live from OpenAlex

Microseismic mapping is a valuable tool for assessing hydraulic fracture stimulations. During a stimulation treatment, borehole, near-surface, or surface geophones record passive seismic data. The microseismic events are thought to be shear failures that occur around the opening of a tensile hydraulic fracture as it grows. Over the past several years, there has been a large growth in the number of hydraulic fracture monitoring surveys, along with the number of vendors who acquire and process microseismic data. Here we discuss two attributes of microseismic data which are associated with the size of the passive event: seismic moment and magnitude.

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)0.004
metaresearch head score (Gemma)0.048
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: none
Teacher disagreement score0.004
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.048
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.002
Science and technology studies0.0000.001
Scholarly communication0.0010.003
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.034
GPT teacher head0.272
Teacher spread0.239 · 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

Citations70
Published2010
Admission routes1
Has abstractyes

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