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Record W2080072662 · doi:10.3189/002214309790794850

Dynamics of a small surge-type glacier using one-dimensional geophysical inversion

2009· article· en· W2080072662 on OpenAlexafffundabout
Lætitia Paoli, Gwenn E. Flowers

Bibliographic record

VenueJournal of Glaciology · 2009
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicCryospheric studies and observations
Canadian institutionsSimon Fraser University
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research ChairsSimon Fraser UniversityParks Canada
KeywordsGeologyGlacierSurgeGeodesyInversion (geology)GeomorphologyKinematicsSeismologyTectonics

Abstract

fetched live from OpenAlex

Abstract We investigate the dynamics of a small surge-type valley glacier as part of a study to characterize glacier response to climate in the Donjek Range, southwest Yukon, Canada. Pole displacements were measured using kinematic GPS techniques during three consecutive summer field seasons. Measured surface velocities range from <10 m a−1over the lower 1500 m of the 5 km long glacier to a maximum of ∼25–35 m a−1over the upper 3500 m. Basal velocities along an approximate flowline are reconstructed from the measured surface velocities using inverse methods. Control tests are used to validate the inversion scheme, and sensitivity tests are performed to evaluate the influence of the flow-law coefficient, shape factor and longitudinal averaging length. Inversion of the real data shows that basal motion accounts for 50–100% of the total surface motion along the flowline. Based on these results, and several other lines of evidence, we suggest this glacier may be undergoing a slow surge.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.082
Threshold uncertainty score0.163

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.038
GPT teacher head0.240
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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations41
Published2009
Admission routes3
Has abstractyes

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