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Record W2766636489 · doi:10.3997/2214-4609.201702121

Geophysical and Geotechnical Characteristics of Champlain Sea Sediments in the Ottawa Valley, Canada

2017· article· en· W2766636489 on OpenAlexaffabout
H Crow, Greg A. Oldenborger, A J -M Pugin, J A Hunter, B Dietiker

Bibliographic record

VenueProceedings · 2017
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeological Modeling and Analysis
Canadian institutionsGeological Survey of Canada
Fundersnot available
KeywordsBedrockGeologyGeotechnical investigationElectrical resistivity tomographySeismic refractionGeophysical surveyGeophysicsStructural basinGround-penetrating radarGeomorphologySeismologyGeotechnical engineeringRadar

Abstract

fetched live from OpenAlex

Summary The soft Champlain Sea sediments of the Ottawa Valley, Canada are susceptible to earthquake-triggered ground failure and contribute to significant amplification of earthquake shaking. We investigate the geophysical and geotechnical properties of Champlain Sea sediments and the underlying shape of the bedrock basin. The objective of the multidisciplinary approach is to characterize the geophysical and geotechnical signatures of high sensitivity clay and silt, and to improve understanding of how these sediments respond to earthquake shaking. Geophysical techniques employed in this study include microtremor recordings, high-resolution seismic profiling, electrical resistivity imaging, and downhole geophysical logging. Geophysical and geotechnical data suggest a bedrock basin up to 98 m deep with a soft sediment fill that exhibits localized evidence of leaching and high sensitivity. Results are consistent with the presence of retrogressive landslide scars in the Breckenridge study area.

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 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)0.000
metaresearch head score (Gemma)0.000
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 score0.276
Threshold uncertainty score0.913

Codex and Gemma teacher scores by category

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

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 head0.014
GPT teacher head0.210
Teacher spread0.196 · 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 teacher head, 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
Published2017
Admission routes2
Has abstractyes

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