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Record W2001462444 · doi:10.1029/2005rg000176

Formation of refrozen snowpack layers and their role in slab avalanche release

2006· article· en· W2001462444 on OpenAlexafffundabout
Bruce Jamieson

Bibliographic record

VenueReviews of Geophysics · 2006
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicCryospheric studies and observations
Canadian institutionsUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsSnowpackSnowSlabGeologyImpact craterMaterials scienceFacet (psychology)Shear (geology)FacetingEvaporationAtmospheric sciencesGeophysicsPetrologyAstrobiologyGeomorphologyMeteorologyCondensed matter physics

Abstract

fetched live from OpenAlex

In a variety of snow climates, numerous slab avalanches release over crusts consisting of refrozen snow. Slab avalanches sometimes release in weak layers of faceted crystals that developed while underlying wet layers froze into crusts, often within a day. Weak layers of faceted crystals can also develop when less permeable and more conductive crusts alter the temperature and vapor pressure gradients. These processes create interfaces where differences in grain radii can contribute to weak bonding. In western Canada, layers of faceted crystals (facet layers) on crusts are most common in early and late winter when thaws and rain are more frequent. Also, thin facet layers occur in spring when surface melting by solar radiation is common. Shear strength tests on facet layers show an initial strength loss during faceting followed by a slow strength increase. The spatial distribution of poorly bonded crusts can be interpreted from the interaction of terrain and meteorology that caused the antecedent wet layer.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
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 head0.014
GPT teacher head0.203
Teacher spread0.189 · 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

Citations61
Published2006
Admission routes3
Has abstractyes

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