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Record W2909216136 · doi:10.4095/212690

Near-surface seismic methods applied to site-response charcterization at an earthquake monitoring station near London, Ontario

2001· report· en· W2909216136 on OpenAlexaffabout
Beatriz Benjumea, S E Pullan, J A Hunter, Robert A. Burns, M Douma, David W. Eaton

Bibliographic record

Venuenot available
Typereport
Languageen
FieldEarth and Planetary Sciences
TopicSeismic Waves and Analysis
Canadian institutionsNatural Resources Canada
Fundersnot available
KeywordsSeismologyGeologySeismic microzonation

Abstract

fetched live from OpenAlex

Near-surface seismic methods have been applied in an area south of London, Ontario, in order to image subsurface structure of the overburden and bedrock surface and to obtain estimates of elastic parameters of these sediments. This work was conducted as a pilot study to determine the seismic site response at a future seismograph site for earthquake monitoring. Two seismic refraction-reflection profiles were acquired on two different terraces cut by the Thames River. The results show two major acoustic impedance boundaries, one within overburden related to the presence of a buried overconsolidated till and the other at the overburden-bedrock contact. The elevation of these two contacts is the same for both studied terraces. A 1-D model has been used to obtain estimates of the variation of fundamental site periods in the survey area. The results of this survey provide the basic information needed to evaluate the site response effects.

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 score0.543
Threshold uncertainty score0.910

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.039
GPT teacher head0.304
Teacher spread0.265 · 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

Citations1
Published2001
Admission routes2
Has abstractyes

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