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Record W4206904139 · doi:10.1002/essoar.10510226.1

Relocation of the 1982 Miramichi, New Brunswick, Canada, aftershock sequence

2022· preprint· en· W4206904139 on OpenAlexafffundabout
Shutian Ma, Dariush Motazedian

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEarth and Planetary Sciences
Topicearthquake and tectonic studies
Canadian institutionsCarleton University
FundersNatural Resources CanadaNatural Sciences and Engineering Research Council of Canada
KeywordsAftershockEpicenterGeologySeismologyRelocationFocal mechanismMagnitude (astronomy)Fault (geology)

Abstract

fetched live from OpenAlex

On 9 January 1982, in the Miramichi region of New Brunswick, Canada, an earthquake with body-wave magnitude (mb) 5.7 occurred. Itwas followed by extensive aftershocks and felt throughout eastern Canada and northeastern USA. Digital seismic stations were not yet commonby 1982. Fortunately, three stations (KLN, EBN and GGN) produced excellent waveform records for the larger aftershocksallowingthese aftershocks to be relocated. For each aftershock,its focal depth was first determinedusing thedepth phase sPg; then, with depth fixed, the epicenter was determinedusing a set of arrival times recorded for the Pg-, Sg-, and Pn-phases at the three stations.Sixty-eight aftershocks were relocated; mostof them occurred in a 5×5 km areaand with depthsof2 to 6 km. The epicentres formed two linear trends in theNE-SW direction. The trends were close to the northeast strike of the focal mechanism of the mainshock and consistent with the topographic trend near the source region. A gap betweenthe trends separated the epicenters into two groups. One group representstherupture area caused by themainshock, and the other groupmight represent the rupture area caused by the mb 5.4principal aftershock.

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)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.030
Threshold uncertainty score0.217

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0040.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.027
GPT teacher head0.219
Teacher spread0.192 · 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
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
Published2022
Admission routes3
Has abstractyes

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