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Record W4205311639 · doi:10.1029/2021gl096501

Retreat of Northern Hemisphere Marine‐Terminating Glaciers, 2000–2020

2022· article· en· W4205311639 on OpenAlexaff
William Kochtitzky, Luke Copland

Bibliographic record

VenueGeophysical Research Letters · 2022
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicCryospheric studies and observations
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsSurgeGlacierGeologyGlacier morphologyIce sheetIce streamNorthern HemispherePhysical geographyIce calvingGreenland ice sheetOceanographyIce capsCryosphereClimatologySea iceGeomorphologyGeography

Abstract

fetched live from OpenAlex

Abstract We mapped the terminus position for every marine‐terminating glacier in the Northern Hemisphere for 2000, 2010, and 2020, including the Greenland Ice Sheet, to provide the first complete measure of their variability. In total, these 1,704 glaciers lost an average of 389.7 ± 1.6 km 2 a −1 (total 7,527 ± 31 km 2 ) from 2000 to 2020 with 123 glaciers becoming no longer marine‐terminating over this period. Overall, 85.3% of glaciers retreated, 2.5% advanced, and the remaining 12.3% did not change outside of uncertainty limits. Outlet glaciers of the Greenland Ice Sheet are responsible for 61.9% of total area loss, although their rate of retreat was 34% less in 2010–2020 than 2000–2010. Glaciers with the largest area loss terminate in ice shelves or ice tongues, are surge‐type, have an unstable basal geometry, or have an unusually wide calving margin.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.134
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.027
GPT teacher head0.267
Teacher spread0.239 · 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.

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

Citations78
Published2022
Admission routes1
Has abstractyes

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