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Record W3046370269 · doi:10.5539/esr.v9n2p85

Correlating DYFI Data With Seismic Microzonation in the Region of Montreal

2020· article· en· W3046370269 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
venuePublished in a venue whose home country is Canada.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueEarth Science Research · 2020
Typearticle
Languageen
FieldEarth and Planetary Sciences
Topicearthquake and tectonic studies
Canadian institutionsNatural Resources CanadaMcGill University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsSeismic microzonationSeismologyMercalli intensity scaleGeologyEarthquake scenarioUrban seismic riskMetropolitan areaPopulationSeismic hazardGeographyPeak ground accelerationGround motion

Abstract

fetched live from OpenAlex

The Western Quebec seismic zone has moderate seismic activity with few historical damaging earthquakes. Nevertheless, recent risk analyses have shown that the combination of a high level of urbanization with soft soil deposits in the metropolitan area of Montreal could lead to significant damage and economic losses. Over the two decades, several projects have been completed to develop a seismic microzonation to identify zones where seismic waves could be amplified. During the same period, Natural Resources Canada developed an internet application to collect reports from the population after an earthquake and to convert them to the Modified Mercalli Intensity scale (MMI). This paper presents a first comparison of the MMI data compiled after eight recent earthquakes felt in Montreal area with the existing zonation in terms of soil classes. It shows that the MMI from individual reports increases when the observer is located in a soft soil zone. Statistics on average MMI over a regular grid confirms this trend. The numerous reports collected through the internet application, and future applications based on data collected from social media, could become a very useful source of information to complement seismic field measurements when developing and validating seismic microzonation maps.

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.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.263
Threshold uncertainty score0.863

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.001
Scholarly communication0.0000.000
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 head0.152
GPT teacher head0.332
Teacher spread0.180 · 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