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Record W3108877811 · doi:10.4095/326974

Induced Seismicity Research Project: a brief summary of 2019-20 accomplishments

2020· report· en· W3108877811 on OpenAlexaffabout
Honn Kao

Bibliographic record

Venuenot available
Typereport
Languageen
FieldEngineering
TopicReservoir Engineering and Simulation Methods
Canadian institutionsNatural Resources Canada
Fundersnot available
KeywordsInduced seismicityGeologySeismologyEngineering

Abstract

fetched live from OpenAlex

The Induced Seismicity Research (ISR) project has a national scope with team members from NRCan offices in Sidney, Vancouver, 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 research universities, to address critical knowledge gaps in the understanding of induced earthquakes and to provide observation-based science to improve regulations on the development of unconventional hydrocarbon resources. Accomplishments during 2019-2020 include: Development of innovative methodologiesfor detection and location of small-magnitude injection-induced earthquakes (IIE); Delineation of source characteristics of significant IIEin BC and AB; Enhanced IIE monitoring for major shale gas basins in Canada; 2019 NRCanDepartmental Achievement Award.

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)0.002
metaresearch head score (Gemma)0.001
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: Other · Consensus signal: none
Teacher disagreement score0.744
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.195
GPT teacher head0.417
Teacher spread0.222 · 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
GenreOther

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
Published2020
Admission routes2
Has abstractyes

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