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Record W2322340310 · doi:10.3189/2012jog11j164

Spatial and temporal variation of ice motion and ice flux from Devon Ice Cap, Nunavut, Canada

2012· article· en· W2322340310 on OpenAlexafffundabout
Wesley Van Wychen, Luke Copland, Laurence Gray, Dave Burgess, Brad Danielson, Martin Sharp

Bibliographic record

VenueJournal of Glaciology · 2012
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicCryospheric studies and observations
Canadian institutionsUniversity of AlbertaUniversity of OttawaGeological Survey of CanadaNatural Resources Canada
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Space AgencyUniversity of Ottawa
KeywordsGeologyGlacierGeodesyIce capsSurgeIce streamIcebergIce calvingGlacier morphologyPhysical geographyGeomorphologyClimatologySea iceCryosphereGeography

Abstract

fetched live from OpenAlex

Abstract Speckle tracking of repeat RADARSAT-2 fine-beam imagery acquired over 24 day periods in March 2009 allowed the creation of updated surface motion maps for the entire Devon Ice Cap, Canada. Error analysis indicates that speckle tracking can determine ice motion to an accuracy of ~5 ma -1 . Comparisons with earlier velocity maps from the mid-1990s and 2000 reveal velocity patterns that largely agree with flow regimes described previously. However, motion determined along East5 Glacier indicates an increase in surface velocities between the studies. Additionally, Southeast2 Glacier has significantly accelerated over the past decade, with velocities greater in 2009 than in the early 1990s along almost the entire length of the glacier. This is likely indicative of a surge. Present-day total mass loss from Devon Ice Cap due to iceberg calving is calculated as 0.40 ± 0.09 Gta -1 , similar to that reported by Burgess and others (2005), with Belcher Glacier accounting for ~42% of the entire loss.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.074
Threshold uncertainty score0.395

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.015
GPT teacher head0.207
Teacher spread0.191 · 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

Citations37
Published2012
Admission routes3
Has abstractyes

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