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Record W7115691218 · doi:10.71846/18-wcee-0417

CANADIAN STRONG MOTION MONITORING AND DATA ACCESS

2025· article· en· W7115691218 on OpenAlexaboutno aff

Bibliographic record

VenueWorld Conference of Earthquake Engineering · 2025
Typearticle
Languageen
FieldComputer Science
TopicSeismology and Earthquake Studies
Canadian institutionsnot available
Fundersnot available
KeywordsEarthquake warning systemSeismometerMotion (physics)Software deploymentUpgradeHazardStrong ground motionChristian ministry

Abstract

fetched live from OpenAlex

Strong motion monitoring across Canada involves numerous organisations. This article summarises the current state (and near-future plans) of strong motion monitoring across Canada and provides information on how to access these data. As of January 2023, the Canadian National Seismograph Network (CNSN) upgrade has been completed. As a part of this upgrade, more than 100 new strong motion instruments (Nanometrics Titans) were deployed at bedrock sites (co-located with weak motion broadband instruments) in high seismic hazard regions of Canada. In addition, 23 stand-alone strong motion instruments were deployed. A major ongoing initiative that will contribute to strong motion monitoring across the country is the deployment of the national Earthquake Early Warning network (led by Natural Resources Canada (NRCan)) that utilises strong motion instruments (Guralp Fortimus and Nanometrics Titans). As of January, 2023, 100+ strong motion instruments have been deployed with an additional 200+ strong motion instruments to be deployed across Canada over the coming year. These instruments are concentrated in the regions of high seismic risk in southwest British Columbia and southwestern Quebec/eastern Ontario. Other organisations collecting strong motion data include BC Hydro (with ~100 strong motion instruments at dam sites and substations across BC), the BC Ministry of Transportation and Infrastructure (BCMOTI) operates the British Columbia Smart Infrastructure Monitoring System (BCSIMS) which includes 100 strong motion sensors and over 400 earthquake sensors installed on 14 BCMOTI owned key bridges. In addition, Ocean Networks Canada has 11 strong motion instruments on the seafloor west of Vancouver Island and 28 strong motion instruments onshore Vancouver Island, and UBC operates dozens of instruments in southwest BC. In eastern Canada, several organisations operate strong motion instruments, including: Hydro-Quebec at dams and substations; Ontario Power Generation and New Brunswick at their nuclear power stations; PWGSC at Parliament Hill; and Gaz Metropolitain at its Montreal LNG plant. Data access is becoming easier - CNSN data are available via NRCan’s FDSN server (currently in beta-testing) at https://earthquakescanada.nrcan.gc.ca/fdsnws/ BCSIMS network data (including BCMoTI and some UBC data) are available via www.bcsims.ca and most ONC strong motion data (OW/NV networks) can be accessed via http://ds.iris.edu/ds/.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.782
Threshold uncertainty score0.884

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.001
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 head0.059
GPT teacher head0.278
Teacher spread0.219 · 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 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
Published2025
Admission routes1
Has abstractyes

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