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Record W3185420512 · doi:10.4095/328457

Induced Seismicity Research Project: highlights of accomplishments in 2020-2021

2021· report· en· W3185420512 on OpenAlexaffabout
Honn Kao

Bibliographic record

Venuenot available
Typereport
Languageen
FieldEngineering
TopicGeotechnical and Geomechanical Engineering
Canadian institutionsNatural Resources Canada
Fundersnot available
KeywordsInduced seismicityGeologySeismology

Abstract

fetched live from OpenAlex

The Induced Seismicity Research (ISR) project has a national scope with team members from NRCan offices in Sidney, Ottawa, and Quebec City. The Project establishes close collaboration with both public and private sectors, including provincial and local governments, crown corporations, professional organizations, and academia, to address critical knowledge gaps in the source process of induced earthquakes and to provide observation-based science to improve regulations on the development of unconventional hydrocarbon resources. Key accomplishments during 2020-2021 include: Adoption of research results into the regulatory framework of induced earthquakes in BC; Publications of research results on source characteristics of significant induced earthquakes in western Canada; Development of innovative methodologies for detection and location of repeating earthquakes and precise earthquake focal depths; Enhanced injection-induced earthquakes (IIE) monitoring for major shale gas basins in BC and AB.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.854
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.002
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 head0.107
GPT teacher head0.352
Teacher spread0.245 · 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.

Study designNot applicable
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
Published2021
Admission routes2
Has abstractyes

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