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Record W3113505011 · doi:10.1017/jog.2020.107

An imbalancing act: the delayed dynamic response of the Kaskawulsh Glacier to sustained mass loss

2020· article· en· W3113505011 on OpenAlexafffundabout
Erik Young, Gwenn E. Flowers, Étienne Berthier, Rebecca Latto

Bibliographic record

VenueJournal of Glaciology · 2020
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicCryospheric studies and observations
Canadian institutionsSimon Fraser University
FundersNatural Sciences and Engineering Research Council of CanadaSimon Fraser UniversityAgence Nationale de la RechercheParks CanadaPolar Knowledge Canada
KeywordsGlacierGlacier mass balanceGeologyGeodetic datumGlacier ice accumulationIce streamClimatologyPhysical geographyGeomorphologyCryosphereGeodesyGeographySea ice

Abstract

fetched live from OpenAlex

Abstract The Kaskawulsh Glacier is an iconic outlet draining the icefields of the St. Elias Mountains in Yukon, Canada. We determine and attempt to interpret its catchment-wide mass budget since 2007. Using SPOT5/6/7 data we estimate a 2007–18 geodetic balance of −0.46 ± 0.17 m w.e. a −1 . We then compute balance fluxes and observed ice fluxes at nine flux gates to examine the discrepancy between the climatic mass balance and internal mass redistribution by glacier flow. Balance fluxes are computed using a fully distributed mass-balance model driven by downscaled and bias-corrected climate-reanalysis data. Observed fluxes are calculated using NASA ITS_LIVE surface velocities and glacier cross-sectional areas derived from ice-penetrating radar data. We find the glacier is still in the early stages of dynamic adjustment to its mass imbalance. We estimate a committed terminus retreat of ~23 km under the 2007–18 climate and a lower bound of 46 km 3 of committed ice loss, equivalent to ~15% of the total glacier volume.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.031
Threshold uncertainty score0.265

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 head0.012
GPT teacher head0.240
Teacher spread0.228 · 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

Citations12
Published2020
Admission routes3
Has abstractyes

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