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Record W2909148619 · doi:10.1038/s41467-018-08195-6

Ocean temperature impact on ice shelf extent in the eastern Antarctic Peninsula

2019· article· en· W2909148619 on OpenAlexaff
Johan Étourneau, Giovanni Sgubin, Xavier Crosta, Didier Swingedouw, Verónica Willmott, Loïc Barbara, Marie-Noëlle Houssais, Stefan Schouten, Jaap S. Sinninghe Damsté, Hugues Goosse, Carlota Escutia, Julien Crespin, Guillaume Massé, Jung‐Hyun Kim

Bibliographic record

VenueNature Communications · 2019
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicCryospheric studies and observations
Canadian institutionsUniversité Laval
FundersEuropean Social FundNederlandse Organisatie voor Wetenschappelijk OnderzoekAgence Nationale de la RechercheKorea Polar Research InstituteEuropean Commission
KeywordsIce shelfPeninsulaOceanographyClimatologyClimate changeGeologySea iceIcebergAntarctic sea iceEnvironmental scienceCryosphereGeography

Abstract

fetched live from OpenAlex

The recent thinning and retreat of Antarctic ice shelves has been attributed to both atmosphere and ocean warming. However, the lack of continuous, multi-year direct observations as well as limitations of climate and ice shelf models prevent a precise assessment on how the ocean forcing affects the fluctuations of a grounded and floating ice cap. Here we show that a +0.3-1.5 °C increase in subsurface ocean temperature (50-400 m) in the northeastern Antarctic Peninsula has driven to major collapse and recession of the regional ice shelf during both the instrumental period and the last 9000 years. Our projections following the representative concentration pathway 8.5 emission scenario from the Fifth Assessment Report of the Intergovernmental Panel on Climate Change reveal a +0.3 °C subsurface ocean temperature warming within the coming decades that will undoubtedly accelerate ice shelf melting, including the southernmost sector of the eastern Antarctic Peninsula.

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 score0.031
Threshold uncertainty score0.417

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 studies0.0000.000
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 head0.019
GPT teacher head0.272
Teacher spread0.253 · 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

Citations76
Published2019
Admission routes1
Has abstractyes

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