MétaCan
Menu
Back to cohort
Record W2154733896

VALIDATING THE PROPAGATION SAW TEST ON THE SLOPE SCALE

2009· article· en· W2154733896 on OpenAlexaffabout
Cameron Ross, Bruce Jamieson

Bibliographic record

VenueInternational Snow Science Workshop, Davos 2009, Proceedings · 2009
Typearticle
Languageen
FieldEnvironmental Science
TopicSmart Materials for Construction
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsScalingScale (ratio)SnowColumn (typography)Snow coverTest (biology)MetreEnvironmental scienceGeologyGeotechnical engineeringMeteorologyForensic engineeringEngineeringGeographyMathematicsTelecommunicationsCartographyGeometryPhysics
DOInot available

Abstract

fetched live from OpenAlex

Over the past few seasons, the Propagation Saw Test (PST) has gained increasing acceptance in some guiding and highway operations in western North America. University of Calgary researchers continued to perform the PST throughout the 2009 winter season in order to further validate the test by building on a previous study. In addition, researchers experimented with column scaling in an attempt to reduce false­stable predictions previously reported for shallow soft slabs. In 2009, more than 600 PSTs were performed in close to 100 snow pits in the Columbia Mountains of British Columbia, Canada to supplement existing data from the previous two winter seasons. At 28 sites in 2009, more than 70 PSTs were performed on 34 layers where fracture propagation was observed (e.g. avalanches or whumpfs) or where fracture initiation was confirmed without propagation. This supplements the 47 sites and 95 tests available to previously validate the PST on the slope scale. An attempt to reduce false­stable predictions of the PST by scaling column length with layer depth below a meter is briefly discussed, supporting the standard test method. A recording standard for the PST is also presented.

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)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.417
Threshold uncertainty score0.940

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0020.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.012
GPT teacher head0.243
Teacher spread0.231 · 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 designBench or experimental
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

Citations1
Published2009
Admission routes2
Has abstractyes

Explore more

Same venueInternational Snow Science Workshop, Davos 2009, ProceedingsSame topicSmart Materials for ConstructionFrench-language works237,207