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Record W6936263877 · doi:10.57757/iugg23-2442

Identifying probable fault planes in the stable continental regions of Canada

2023· article· en· W6936263877 on OpenAlexaffabout

Bibliographic record

VenuePublication Database GFZ (GFZ German Research Centre for Geosciences) · 2023
Typearticle
Languageen
FieldEarth and Planetary Sciences
Topicearthquake and tectonic studies
Canadian institutionsNatural Resources Canada
Fundersnot available
KeywordsActive faultFault (geology)AftershockSeismic hazardHazardSeismotectonicsMagnitude (astronomy)Seismic risk

Abstract

fetched live from OpenAlex

<!--!introduction!--><b></b> Seismic hazard assessment has advanced beyond relying solely on magnitude recurrence rates to incorporating additional parameters, such as faults and deformation rates.&nbsp;&nbsp; In the stable craton of Canada, active faults have been difficult to identify as there is only one earthquake with a known surface rupture (northern Quebec, 1989).&nbsp;&nbsp; Additional sources of information, such as GNSS and INSAR, have thus far been of limited value for hazard assessment in this region because of poor spatial coverage and the relatively modest sizes of recent earthquakes. &nbsp;Nevertheless, the region comprises several active seismic zones with well recorded earthquakes and large earthquakes have occurred historically.&nbsp;&nbsp; Building on an initial study of the Western Quebec Seismic Zone, statistical analyses of focal mechanisms focusing on modal values (e.g. Salvado-Gálvez et al. 2020) in all seismically active regions of southeastern Canada and the eastern Canadian Arctic are applied to determine probable fault planes. &nbsp;In the Canadian craton, this method has been successful in determining strike direction and dip angles but the results for dip direction have been largely equivocal.&nbsp; The results, however, have been useful for developing weighting schemes for incorporating dip directions into the hazard assessment.&nbsp;&nbsp; Additionally, relocations of active aftershock sequences in some seismic zones provide information about fault orientations.&nbsp; Although the impetus of this study is to provide input to future Canadian seismic hazard models, the results will also provide input to other research topics, such as associating earthquakes with actual faults.

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)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.482
Threshold uncertainty score0.643

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.003
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
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 head0.074
GPT teacher head0.324
Teacher spread0.250 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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
Published2023
Admission routes2
Has abstractyes

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