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Record W2588908043 · doi:10.1088/1748-9326/aa5b04

Mass budget of the glaciers and ice caps of the Queen Elizabeth Islands, Canada, from 1991 to 2015

2017· article· en· W2588908043 on OpenAlexaboutno aff
Romain Millan, J. Mouginot, Eric Rignot

Bibliographic record

VenueEnvironmental Research Letters · 2017
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicCryospheric studies and observations
Canadian institutionsnot available
Fundersnot available
KeywordsIce fieldGlacierIce streamGlacier mass balanceCryosphereClimatologySea iceGeologyEnvironmental scienceAtmospheric sciencesPhysical geographyGeographyGeomorphology

Abstract

fetched live from OpenAlex

Recent studies indicate that the glaciers and ice caps in Queen Elizabeth Islands (QEI), Canada have experienced an increase in ice mass loss during the last two decades, but the contribution of ice dynamics to this loss is not well known. We present a comprehensive mapping of ice velocity using a suite of satellite data from year 1991 to 2015, combined with ice thickness data from NASA Operation IceBridge, to calculate ice discharge. We find that ice discharge increased significantly after 2011 in Prince of Wales Icefield, maintained or decreased in other sectors, whereas glacier surges have little impact on long-term trends in ice discharge. During 1991–2005, the QEI mass loss averaged 6.3 ± 1.1 Gt yr ^−1 , 52% from ice discharge and the rest from surface mass balance (SMB). During 2005–2014, the mass loss from ice discharge averaged 3.5 ± 0.2 Gt yr ^−1 (10%) versus 29.6 ± 3.0 Gt yr ^−1 (90%) from SMB. SMB processes therefore dominate the QEI mass balance, with ice dynamics playing a significant role only in a few basins.

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 score0.299
Threshold uncertainty score0.520

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 studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.019
GPT teacher head0.242
Teacher spread0.223 · 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

Citations51
Published2017
Admission routes1
Has abstractyes

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