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Record W7057945507

Locations of the 1982 Miramichi (Canada) Aftershocks : Implication of Two Rupture Regions Activated

2020· other· en· W7057945507 on OpenAlexaboutno aff

Bibliographic record

VenueBiblioBoard Library Catalog (Open Research Library) · 2020
Typeother
Languageen
FieldPhysics and Astronomy
TopicMagnetic confinement fusion research
Canadian institutionsnot available
Fundersnot available
KeywordsAftershockIntraplate earthquakeEpicenterForeshockSequence (biology)Event (particle physics)Magnitude (astronomy)Arrival time
DOInot available

Abstract

fetched live from OpenAlex

On 9 January 1982, in the Miramichi region of New Brunswick, Canada, an earthquake with mb 5.7 occurred. It was followed by extensive aftershocks and felt throughout eastern Canada and north-eastern USA. Since this earthquake occurred in an uninhabited region, the damage was minor. Due to an mb 5.7 event is rare in north-eastern America, investigating it and its aftershocks is important for understanding intraplate seismicity. Digital seismic stations were not yet common by 1982. Fortunately, four seismic phases at three stations could be used to locate larger aftershocks. A simplified master-event location method combined with regional depth-phase modeling was used to locate aftershocks. For each aftershock its focal depth was first determined using a depth phase; then, with the depth fixed, the epicenter was determined using the four arrival time readings measured at the same three stations. The located aftershocks were divided into three groups. In each group the earthquake numbers are similar, but the majority of the energy was released in one group. The epicenters formed two trends in the NE–SW direction, implying that the Miramichi earthquake sequence activated two rupture regions.

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 score0.103
Threshold uncertainty score0.207

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.032
GPT teacher head0.302
Teacher spread0.270 · 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
Published2020
Admission routes1
Has abstractyes

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