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Record W2803368100 · doi:10.1029/2017jf004304

Six Decades of Glacial Mass Loss in the Canadian Arctic Archipelago

2018· article· en· W2803368100 on OpenAlex
Brice Noël, Willem Jan van de Berg, Stef Lhermitte, Bert Wouters, Nicole Schaffer, M. R. van den Broeke

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueJournal of Geophysical Research Earth Surface · 2018
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicCryospheric studies and observations
Canadian institutionsUniversity of OttawaEnvironment and Climate Change Canada
FundersNederlandse Organisatie voor Wetenschappelijk Onderzoek
KeywordsArchipelagoGlacierArcticPhysical geographyGeologyFirnClimatologyArctic ice packGlacial periodTundraOceanographyGeographyGeomorphology

Abstract

fetched live from OpenAlex

The Canadian Arctic Archipelago comprises multiple small glaciers and ice caps, mostly concentrated on Ellesmere and Baffin Islands in the northern (NCAA, Northern Canadian Arctic Archipelago) and southern parts (SCAA, Southern Canadian Arctic Archipelago) of the archipelago, respectively. Because these glaciers are small and show complex geometries, current regional climate models, using 5‐ to 20‐km horizontal resolution, do not properly resolve surface mass balance patterns. Here we present a 58‐year (1958–2015) reconstruction of daily surface mass balance of the Canadian Arctic Archipelago, statistically downscaled to 1 km from the output of the regional climate model RACMO2.3 at 11 km. By correcting for biases in elevation and ice albedo, the downscaling method significantly improves runoff estimates over narrow outlet glaciers and isolated ice fields. Since the last two decades, NCAA and SCAA glaciers have experienced warmer conditions (+1.1°C) resulting in continued mass loss of 28.2 ± 11.5 and 22.0 ± 4.5 Gt/year, respectively, more than doubling (11.9 Gt/year) and doubling (11.9 Gt/year) the pre‐1996 average. While the interior of NCAA ice caps can still buffer most of the additional melt, the lack of a perennial firn area over low‐lying SCAA glaciers has caused uninterrupted mass loss since the 1980s. In the absence of significant refreezing capacity, this indicates inevitable disappearance of these highly sensitive glaciers.

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.

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)0.002
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 score0.509
Threshold uncertainty score0.688

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.056
GPT teacher head0.316
Teacher spread0.260 · 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