MétaCan
Menu
Back to cohort
Record W2144658832 · doi:10.1139/t09-058

Arctic coastal retreat through block failure

2009· article· en· W2144658832 on OpenAlexaffvenue
Md. Azharul Hoque, Wayne H. Pollard

Bibliographic record

VenueCanadian Geotechnical Journal · 2009
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicClimate change and permafrost
Canadian institutionsMcGill University
Fundersnot available
KeywordsPermafrostGeologyArcticGeotechnical engineeringBlock (permutation group theory)Slope stabilityStability (learning theory)Ecological nicheGeomorphologyGeometryMathematicsOceanographyEcology

Abstract

fetched live from OpenAlex

This study investigates the mechanics of block failure in frozen bluffs underlain by permafrost along Arctic coasts. Different block failure modes with and without thermoerosional niches and ice wedges are identified. A comprehensive analytical model is developed by coupling slope stability analysis with the progressive formation of a thermoerosional niche and the existence of ice wedges in the perennially frozen backshore area. Model computations involve three steps. First, the stability of frozen cliffs is examined by calculating the factor of safety based on slope analysis using the strength of permafrost soil. Second, in the presence of thermoerosional niches at the base of frozen cliffs, the failure modes and critical niche depths are determined by applying the moving boundary of a developing thermoerosional niche to the stability analysis. Finally, the effects of ice wedges are examined by imposing a change in strength conditions related to the existence of ice wedges at different locations in the potential failure region. Different potential failure modes and the critical combination of features contributing to block failure occurrences in Arctic coastal bluffs are identified through model calculations. Nondimensional parameters, regression equations, and graphs are derived to be used for determining the block failure potential for Arctic coasts.

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 categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.562
Threshold uncertainty score0.990

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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0110.000

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 head0.024
GPT teacher head0.226
Teacher spread0.202 · 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.

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

Citations83
Published2009
Admission routes2
Has abstractyes

Explore more

Same venueCanadian Geotechnical JournalSame topicClimate change and permafrostFrench-language works237,207