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Record W2964774221 · doi:10.4095/314803

Felt reports for the 1870 magnitude 6.5 earthquake, Charlevoix, Quebec

2019· report· en· W2964774221 on OpenAlexaffabout
Maurice Lamontagne, K. B. S. Burke, Didier Perret

Bibliographic record

Venuenot available
Typereport
Languageen
FieldComputer Science
TopicSeismology and Earthquake Studies
Canadian institutionsNatural Resources Canada
Fundersnot available
KeywordsMagnitude (astronomy)Earthquake magnitudeSeismologyGeologyPhysicsMathematicsAstronomyGeometry

Abstract

fetched live from OpenAlex

The 20 October 1870 magnitude 6.6 Charlevoix Earthquake occurred at around 11:30am local time. The main shock was felt from Nova Scotia to the east to Sault Ste. Marie to the west and as far south as Cincinnati, Ohio, almost 1500 km from the epicenter. Newspapers in Quebec City reported the extensive damage caused in Charlevoix by this earthquake. Based on these accounts, we know that the earthquake was sufficiently powerful to cause a few landslides and soil liquefaction in the epicentral region. Damage was reported to many houses, including complete destruction of some dwellings, in Baie-Saint-Paul, Saint-Urbain, Ile aux Coudres and Les Éboulements. It is one of five known magnitude 6-7 earthquakes that have occurred in the Charlevoix Seismic Zone between 1663 and present. This Open File Report presents the macroseismic information and its ratings on the Modified Mercalli Scale for a total of 192 locations in Canada and the United States. For each locality, the felt information is rated on the Modified Mercalli intensity (MMI) scale and tabulated in a Microsoft Excel sheet. The text of many of the newspaper accounts were copied and when possible, the newspaper clipping was scanned. The Open File also provides a GoogleEarth kmz file that allows the felt information reports to be viewed in a spatial tool.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.184
Threshold uncertainty score0.616

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0050.007
Science and technology studies0.0020.000
Scholarly communication0.0030.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.1840.024

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 head0.042
GPT teacher head0.285
Teacher spread0.243 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations1
Published2019
Admission routes2
Has abstractyes

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