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Record W1582184173 · doi:10.1002/2013jf002838

Changes in accumulation-area firn stratigraphy and meltwater flow during a period of climate warming: Devon Ice Cap, Nunavut, Canada

2013· article· en· W1582184173 on OpenAlexaffabout
Gabrielle Gascon, Martin Sharp, David Burgess, Peter Bezeau, Andrew B. G. Bush

Bibliographic record

VenueJournal of Geophysical Research Earth Surface · 2013
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicCryospheric studies and observations
Canadian institutionsGeological Survey of CanadaNatural Resources CanadaUniversity of Alberta
Fundersnot available
KeywordsFirnMeltwaterGeologyGeomorphologyIce coreSnowClimatology

Abstract

fetched live from OpenAlex

[1] To document climate-driven changes in firn stratigraphy and their implications for meltwater flow patterns within firn on the Devon Ice Cap, Nunavut, during the 21st century summer warming, 500 MHz ground-penetrating radar (GPR) surveys were conducted along a 40 km transect in each spring from 2007 to 2012. These linear GPR surveys were supplemented by four 190 m by 100 m GPR grid surveys and 36 firn cores. Increased meltwater percolation and infiltration ice formation associated with high surface melt rates since 2005 modified the firn stratigraphy substantially over a horizontal distance of nearly 30 km. The most dramatic change involved the growth of a thick ice layer within the firn body. This layer grew primarily by upward accretion over an initial widespread ice layer formed during summer 2005. It thickened by between 0.5 and 4.5 m over the study period and filled much of the pore volume in the upper part of the firn, reducing vertical percolation of meltwater into deeper sections of the firn and thus the water storage potential of much of the firn reservoir. Heterogeneous percolation of surface meltwater promoted by rolling topography played an important role in meltwater infiltration and drainage, encouraging lateral flow at the tops of small hills and ponding and refreezing of meltwater beneath surface depressions.

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 score0.488
Threshold uncertainty score0.698

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 head0.045
GPT teacher head0.280
Teacher spread0.235 · 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

Citations46
Published2013
Admission routes2
Has abstractyes

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