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Record W2293879242 · doi:10.1002/2016gl067759

Ice mass loss in Greenland, the Gulf of Alaska, and the Canadian Archipelago: Seasonal cycles and decadal trends

2016· article· en· W2293879242 on OpenAlex
Christopher Harig, Frederik J. Simons

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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueGeophysical Research Letters · 2016
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeophysics and Gravity Measurements
Canadian institutionsnot available
FundersNational Oceanic and Atmospheric AdministrationNational Science Foundation
KeywordsGroenlandiaArchipelagoGlacierGreenland ice sheetIcebergGeologyOceanographyClimatologyArctic ice packSea iceFuture sea levelIce coreCryosphereIce sheetPhysical geographyAntarctic sea iceGeographyGeomorphology

Abstract

fetched live from OpenAlex

Abstract Over the past several decades mountain glaciers and ice caps have been significant contributors to sea level rise. Here we estimate the ice mass changes in the Canadian Archipelago, the Gulf of Alaska, and Greenland since 2003 by analyzing time‐varying gravimetry data from the Gravity Recovery and Climate Experiment. Prior to 2013, interannual ice mass variability in the Gulf of Alaska and in regions around Greenland remains within the average estimated over the whole data span. Beginning in summer 2013, ice mass in regions around Greenland departs positively from its long‐term trend. Over Greenland this anomaly reached almost 500 Gt through the end of 2014. Overall, long‐term ice mass loss from Greenland and the Canadian Archipelago continues to accelerate, while losses around the Gulf of Alaska region continue but remain steady with no significant acceleration.

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)0.001
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 score0.213
Threshold uncertainty score0.678

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.030
GPT teacher head0.263
Teacher spread0.233 · 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