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Record W2958643348 · doi:10.1130/g46201.1

Are submarine landslides an underestimated hazard on the western North Atlantic passive margin?

2019· article· en· W2958643348 on OpenAlexaffabout
Alexandre Normandeau, D C Campbell, David J. W. Piper, Kimberley A. Jenner

Bibliographic record

VenueGeology · 2019
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeology and Paleoclimatology Research
Canadian institutionsGeological Survey of CanadaNatural Resources Canada
Fundersnot available
KeywordsGeologySubmarine landslideLandslideHoloceneSubmarineBathymetrySubmarine pipelineContinental marginOceanographyPopulationGeomorphologyPhysical geographySeismologyGeographyTectonics

Abstract

fetched live from OpenAlex

Abstract The western North Atlantic passive margin is considered relatively stable, with few slope instabilities recognized during the Holocene. However, new multibeam bathymetry mapping and sediment core acquisition off eastern Canada indicate that previously unidentified, large, submarine landslide events occurred during the Late Holocene, between 4 and 1.5 ka. The recognition of these new gravitational events, in addition to the well-known C.E. 1929 Grand Banks earthquake-induced landslide, indicates that approximately one large landslide event per 1000 years has occurred offshore eastern Canada within the past 4000 years, a much shorter recurrence interval than hitherto reported. This Late Holocene recurrence rate is also similar to active margins around the world and is likely due to the under-consolidation and resultant instability of Scotian Slope sediments attributable to high glacial sedimentation rates. The discovery of these new Late Holocene landslides was made possible through detailed examination of cores recovered from the lower slope. These results demonstrate that submarine landslide hazard has been underestimated on the western North Atlantic margin—home to significant submarine infrastructure and proximal to a large coastal population.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.115
Threshold uncertainty score0.995

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)0.0060.008

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 head0.028
GPT teacher head0.245
Teacher spread0.217 · 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; both teacher heads agree on what is shown here.

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

Citations29
Published2019
Admission routes2
Has abstractyes

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