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Record W1891800431 · doi:10.1002/2015gl063455

Hydraulic fracturing and the Crooked Lake Sequences: Insights gleaned from regional seismic networks

2015· article· en· W1891800431 on OpenAlexaffabout
Ryan Schultz, Virginia Stern, Mark Novakovic, Gail M. Atkinson, Yu Jeffrey Gu

Bibliographic record

VenueGeophysical Research Letters · 2015
Typearticle
Languageen
FieldEarth and Planetary Sciences
Topicearthquake and tectonic studies
Canadian institutionsUniversity of AlbertaWestern University
Fundersnot available
KeywordsInduced seismicityGeologyHydraulic fracturingSeismologySeismometerSequence (biology)Paleontology

Abstract

fetched live from OpenAlex

Abstract Within central Alberta, Canada, a new sequence of earthquakes has been recognized as of 1 December 2013 in a region of previous seismic quiescence near Crooked Lake, ~30 km west of the town of Fox Creek. We utilize a cross‐correlation detection algorithm to detect more than 160 events to the end of 2014, which is temporally distinguished into five subsequences. This observation is corroborated by the uniqueness of waveforms clustered by subsequence. The Crooked Lake Sequences have come under scrutiny due to its strong temporal correlation (>99.99%) to the timing of hydraulic fracturing operations in the Duvernay Formation. We assert that individual subsequences are related to fracturing stimulation and, despite adverse initial station geometry, double‐difference techniques allow us to spatially relate each cluster back to a unique horizontal well. Overall, we find that seismicity in the Crooked Lake Sequences is consistent with first‐order observations of hydraulic fracturing induced seismicity.

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)0.001
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 score0.605
Threshold uncertainty score0.794

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
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 head0.056
GPT teacher head0.271
Teacher spread0.215 · 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

Citations111
Published2015
Admission routes2
Has abstractyes

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