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Record W2103984182

Dynamics of a small surge-type glacier, St. Elias Mountains, Yukon Territory, Canada: characterization of basal motion using 1-D geophysical inversion

2009· dissertation· en· W2103984182 on OpenAlexfundaboutno aff
Lætitia Paoli, Gwenn E. Flowers

Bibliographic record

VenueSummit (Simon Fraser University) · 2009
Typedissertation
Languageen
FieldEarth and Planetary Sciences
TopicCryospheric studies and observations
Canadian institutionsnot available
FundersSimon Fraser UniversityNatural Sciences and Engineering Research Council of CanadaCanada Research Chairs
KeywordsGlacierSurgeGeologyInversion (geology)Tidewater glacier cycleGeodesyGlacier ice accumulationClimatologyGlacier mass balanceGeomorphologyGlaciologyGeophysicsSeismologyIce streamTectonicsCryosphereSea ice
DOInot available

Abstract

fetched live from OpenAlex

The dynamics of a small surge-type glacier are investigated as part of a study to characterize glacier response to climate in southwest Yukon Territory, Canada.DEMs of the glacier surface and bed are constructed from surface elevation and ice thickness data.Measured surface velocities are higher than expected for a surge-type glacier in its quiescent phase over the upper 3500 m of the 5 km-long glacier, but much lower than typical surge velocities.Flowline basal velocities are reconstructed from the measured surface velocities using a 1-D geophysical inverse model.Control tests are used to validate the inversion scheme, and sensitivity tests are performed to evaluate the influence of uncertain parameters.Inversion of the measured surface velocities reveals an unusually high contribution of basal motion to the overall motion.Based on these results and several other lines of evidence, we suggest that the glacier may be undergoing a slow surge.iiiFirst of all, I would like to thank my supervisor, Gwenn Flowers, for her guidance and support during the three years I spent at SFU. Gwenn not only taught me a great deal about glaciology, she also has been a great advisor and friend.I am grateful for her outstanding guidance in all academic matters, and for the friendly and stimulating environment she has created throughout my studies.Her constant encouragements, her constructive criticism and her open-door policy were very much apreciated.I am also grateful to my other comittee member, Andrew Calvert, for his time and his constructive feedback on my work and to Martin Truffer for reviewing this thesis.I would like to thank all members of the SFU glaciology group for their advice on matters ranging from programming to conference presentations and for creating an enjoyable

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.058
Threshold uncertainty score0.116

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
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 head0.013
GPT teacher head0.186
Teacher spread0.174 · 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

Citations4
Published2009
Admission routes2
Has abstractyes

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