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Record W4386315917 · doi:10.1139/as-2022-0045

Evolution of the dynamics of Airdrop Glacier, western Axel Heiberg Island, over a seven-decade-long advance

2023· article· en· W4386315917 on OpenAlexafffundvenueabout
Benoît Lauzon, Luke Copland, Wesley Van Wychen, William Kochtitzky, Robert McNabb

Bibliographic record

VenueArctic Science · 2023
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicCryospheric studies and observations
Canadian institutionsUniversity of WaterlooUniversity of Ottawa
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of ManitobaArcticNetUniversity of Ottawa
KeywordsGlacierGlacier terminusGeologyArcticSurgeGlacier mass balanceThinningSatelliteTidewater glacier cyclePhysical geographyDynamics (music)ClimatologyOceanographyIce streamGeographyGeomorphologyCryosphereSea ice

Abstract

fetched live from OpenAlex

Various remotely sensed data, including historical aerial photographs, declassified intelligence satellite photographs, optical satellite imagery, and synthetic aperture radar data, were used to undertake the first comprehensive reconstruction of the dynamics of Airdrop Glacier on Axel Heiberg Island, Nunavut. Observations show a continuous terminus advance totalling ∼6 km since 1950 and notably less variability in its surface velocities in comparison to adjacent Iceberg Glacier. This advance is concurrent with relatively high flow rates over its entire surface, resulting in significant thickening near the terminus and thinning at higher elevations. Velocities have more than halved from the mid-2000s to 2021, but without any definitive evidence of previous flow instabilities, we cannot confirm whether Airdrop's behaviour is cyclic in nature and therefore characteristic of a surge. Instead, Airdrop Glacier could be experiencing a delayed response to the positive mass balance conditions of the Little Ice Age, which could also explain the advance of other nearby glaciers. Its recent slowdown could then be indicative of a gradual adjustment to recent climatic conditions. This study highlights the need for comprehensive studies of glacier dynamics in the Canadian Arctic to improve our understanding of the factors triggering dynamic instabilities and causing the observed variety of behaviours.

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 score0.072
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.001
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 head0.012
GPT teacher head0.235
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

Citations6
Published2023
Admission routes4
Has abstractyes

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