MétaCan
Menu
Back to cohort
Record W2040549464 · doi:10.1029/2007jb005238

Recent changes in thickness of the Devon Island ice cap, Canada

2008· article· en· W2040549464 on OpenAlexaffabout
David Burgess, Martin Sharp

Bibliographic record

VenueJournal of Geophysical Research Atmospheres · 2008
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicCryospheric studies and observations
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsGlacierGeologyFlux (metallurgy)Ice capsAblation zoneElevation (ballistics)Structural basinGreenland ice sheetClimate changeSea levelGeomorphologyPhysical geographyClimatologyOceanographyGeographyGeometry

Abstract

fetched live from OpenAlex

Long‐term rates of thickness change were derived at several spatial scales using a variety of methods for most of the Devon Island ice cap, Nunavut, Canada. Basin‐wide thickness change calculations were derived for the accumulation zones of all major drainage basins as the area‐averaged volume difference between balance and InSar fluxes at the altitude of the long‐term equilibrium line (ELA). Thickness changes for ablation zones were derived as a function of the surface mass balance, flux across the EL and calving flux, averaged across the ablation areas. Average rates of thickness change are near zero in the accumulation zones of the northern and southwestern basins but reach −0.23 ± 0.11 m a−1 w.e. in the southeast basin due to dynamic thinning. Thickness changes were also estimated along five major outlet glaciers as a function of flux divergence and net surface mass balance and along the Belcher Glacier by comparing elevation values derived from 1960s aerial photography with those derived from 2005 NASA Airborne Topographic Mapper (ATM) surveys. Ice dynamics have had a significant influence on the pattern of thickness change of all outlet glaciers examined in this study. Volume changes derived from the basin‐wide values indicate a net loss of −76.8 ± 7 km3 water equivalent from the main portion of the ice cap from 1960 to 1999, contributing 0.21 ± 0.02 mm to global sea level over this time. This value is ∼44% greater than previous estimates of volume change based on volume‐area scaling methods and surface mass balance alone.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.030
Threshold uncertainty score0.091

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.000
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 head0.051
GPT teacher head0.277
Teacher spread0.226 · 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 source (direct Gemma or distilled Codex), 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

Citations22
Published2008
Admission routes2
Has abstractyes

Explore more

Same venueJournal of Geophysical Research AtmospheresSame topicCryospheric studies and observationsFrench-language works237,207