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Record W4283837829 · doi:10.1017/jog.2022.47

Multi-decadal elevation changes of the land terminating sector of West Greenland

2022· article· en· W4283837829 on OpenAlexfundno aff
J. Saito, Toby Meierbachtol, J. T. Harper

Bibliographic record

VenueJournal of Glaciology · 2022
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicCryospheric studies and observations
Canadian institutionsnot available
FundersOffice of Experimental Program to Stimulate Competitive ResearchNuclear Waste Management OrganizationNational Science Foundation
KeywordsElevation (ballistics)GeologyGreenland ice sheetForcing (mathematics)Ice sheetClimate changeClimatologyDigital elevation modelIce-sheet modelIce coreFuture sea levelIce streamPhysical geographyCryosphereSea iceGeomorphologyOceanographyGeographyRemote sensing

Abstract

fetched live from OpenAlex

Abstract Regional assessments of ice elevation change provide insight into the processes controlling an ice sheet's geometric response to climate forcing. In Southwest Greenland's land terminating sector (SWLTS), it is presumed that ice surface elevation changes result solely from changing surface mass balance (SMB). Here we test this assumption by developing a multi-decadal (1985–2017) record of elevation change from digital elevation models (DEMs) and comparing it to regional climate model output and available records of ice speed. The SWLTS thinned by >12 m on average over the full 32-year period, but the change was highly variable in time and space. Thinning was amplified in the central region of the SWLTS, relative to the north and south. During 1985–2007, the north and south regions demonstrated net thickening while the central region thinned. Regional differences in elevation change are inconsistent with SMB anomalies, indicating that enhanced ice flow in the north and south contributed to thickening during this early time interval. While clear validation in the south is prevented by incomplete velocity data, historical surface speeds in the north were elevated. These findings support the interpretation that changing ice flow can influence ice surface elevation in the slow-moving SWLTS.

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 score0.004
Threshold uncertainty score0.696

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)0.0010.000

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 head0.033
GPT teacher head0.238
Teacher spread0.205 · 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

Citations0
Published2022
Admission routes1
Has abstractyes

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