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Record W1984272292 · doi:10.5194/adgeo-14-211-2008

Catastrophic glacial multi-phase mass movements: a special type of glacial hazard

2008· article· en· W1984272292 on OpenAlexaffabout
Dmitry Petrakov, Sergey Chernomorets, Stephen G. Evans, Olga Tutubalina

Bibliographic record

VenueAdvances in geosciences · 2008
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicCryospheric studies and observations
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsGlacierGeologyHazardGlacial periodMass movementNatural hazardPhysical geographyGlacier terminusEvent (particle physics)ClimatologySeismologyGeographyGeomorphologyIce streamLandslideCryosphereOceanography

Abstract

fetched live from OpenAlex

Abstract. Many glacier-related hazards are well typified and studied, but some events stand out from conventional classifications. The Kolka-Karmadon catastrophic event on 20 September 2002 in North Ossetia, North Caucasus, Russia is used as an example of a complex glacier failure exhibiting characteristics such as high mobility, long runout, ultrarapid movement and multiphase behaviour. We consider terminology protocol for glacier hazard classification and then, using the Kolka-Karmadon event and several other examples from around the world, we propose a new term for this family of events. Catastrophic glacier multi-phase mass movement (CGMM) is described and further illustrated by eight major events from Russia, Georgia, Peru, Chile, and Canada. CGMM have a combination of specific features: extraordinary velocities and long-distance runout despite low path angle; progressive fluidisation along travel path; superelevation and run-up of the moving mass, air blast wave in the avalanche flow phase; entrainment of available materials in its path, and the repeated nature of the event. CGMM events may affect areas remote from glaciers which were previously considered as safe.

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 score0.044
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.035
GPT teacher head0.289
Teacher spread0.253 · 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

Citations53
Published2008
Admission routes2
Has abstractyes

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