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Record W76061820

Empirical Analysis of Snow Deformation Below Penetrometer Tips

2006· article· en· W76061820 on OpenAlexaff
James Floyer, Bruce Jamieson

Bibliographic record

VenueProceedings of the 2006 International Snow Science Workshop, Telluride, Colorado · 2006
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicCryospheric studies and observations
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsSnowPenetrometerGeologyDeformation (meteorology)SnowpackSnow fieldGeotechnical engineeringGeomorphologySnow coverSoil science
DOInot available

Abstract

fetched live from OpenAlex

Recent field observations suggest that when an object, such as a digital snow penetrometer, is pushed through snow, a zone of densified snow develops in front of it. It is this zone of densified snow, rather than the actual tip of the object itself, that impacts on newly encountered snow as the object is pushed deeper into the snowpack. The concept of a compacted zone is introduced to describe this zone of snow. This is a sub-region of the broader deformation zone that encompasses all snow deformation below the tip of the penetrating object. The shape of both the deformation zone and compacted zone is influenced by the shape of the object’s tip but also by the density, temperature, moisture content, grain size and grain shape of the snow through which the object is being pushed. The compacted zone effect is described and the impact on snow deformation of different snow densities and different tip shapes is preliminarily assessed. The use of particle image velocimetry in conjunction with a moving body coordinate system is presented as a useful tool for analysing deformation patterns for moving objects through uniform snow. The importance of this effect for penetrometer tip design and assessment of vertical resolution is discussed. Data is taken from a series of video and rapid-fire still camera shots of different shaped penetrometer tips being pushed through a clear, stiff plastic box filled with snow. Snow confinement along the side of the snow box is identified as a limitation of this technique.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.039
Threshold uncertainty score0.765

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.004
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.018
GPT teacher head0.248
Teacher spread0.230 · 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

Citations9
Published2006
Admission routes1
Has abstractyes

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Same venueProceedings of the 2006 International Snow Science Workshop, Telluride, ColoradoSame topicCryospheric studies and observationsFrench-language works237,207