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Record W4388931188 · doi:10.3997/2214-4609.202385028

Induced Seismicity Red-light Thresholds at the Alberta No. 1 Geothermal Project Site

2023· article· en· W4388931188 on OpenAlexaffabout
Ali Yaghoubi, Ryan Schultz, Catherine J. Hickson, Andrew Wigston, Maurice B. Dusseault

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldDecision Sciences
TopicRisk and Safety Analysis
Canadian institutionsUniversity of WaterlooNatural Resources Canada
Fundersnot available
KeywordsInduced seismicityGeothermal gradientRisk managementStructural basinSeismic riskRisk analysis (engineering)Environmental scienceSeismologyGeologyBusinessGeomorphologyFinanceGeophysics

Abstract

fetched live from OpenAlex

Summary The Alberta No. 1 geothermal project (ABNo1) represents a promising venture in harnessing geothermal energy potential within the Western Canadian Sedimentary Basin (WCSB). ABNo1 faces the challenge of managing induced seismicity, a concern exacerbated by past experiences of earthquake activity in the region due to underground fluid injection. This paper presents a risk-informed Traffic Light Protocol (TLP) approach to address injection-induced seismicity risks. By quantifying Local Personal Risk (LPR), damage risk, and nuisance risk within the project area, red-light thresholds are established based on a comprehensive risk-based framework. The integrated TLP combines these individual risk maps, allowing for a flexible and conservative approach to risk management. The results indicate a red-light threshold of M L =3.5, with specific thresholds for different risk metrics. These findings contribute to enhancing the safety and effectiveness of geothermal development projects in the region.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.559
Threshold uncertainty score0.876

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.092
GPT teacher head0.362
Teacher spread0.270 · 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

Citations0
Published2023
Admission routes2
Has abstractyes

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