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Record W4386663918 · doi:10.4095/328951

Développement d'un système d'alerte précoce pour les tremblements de terre du Québec

2021· report· en· W4386663918 on OpenAlexaffabout
Maurice Lamontagne

Bibliographic record

Venuenot available
Typereport
Languageen
FieldComputer Science
TopicSeismology and Earthquake Studies
Canadian institutionsNatural Resources Canada
Fundersnot available
KeywordsSeismometerSeismologyEpicenterWarning systemGeneral partnershipEarthquake warning systemGeographyGeologyBusinessTelecommunicationsEngineeringFinance

Abstract

fetched live from OpenAlex

Several regions of the world already have or are in the process of developing an early warning system (EWS) for earthquakes. As is well known, earthquakes cannot be predicted in the short term. However, an EWS is based on the principle that when a strong earthquake occurs, the initial seismic waves detected by seismographs near the epicentre can be quickly analysed. Once analyzed automatically, an alarm signal can be sent to more distant areas before damaging seismic waves arrive. This alert can then be used to take action before the seismic waves arrive (such as stopping industrial activities for example). In Canada, these technologies are being developed for the Pacific region and Eastern Canada. Quebec is particularly interesting because earthquakes of magnitude 5 are felt at great distances, which increases the warning time when an earthquake occurs. Natural Resources Canada (NRCan) will lead this initiative, in partnership with provincial collaborators. The private sector will also be involved through the development of software and applications. NRCan is therefore reaching out to potential partners in such an earthquake warning system.

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: Other · Consensus signal: none
Teacher disagreement score0.481
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
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.047
GPT teacher head0.279
Teacher spread0.232 · 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
Published2021
Admission routes2
Has abstractyes

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Same topicSeismology and Earthquake StudiesFrench-language works237,207