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Record W3151507768 · doi:10.1038/s41467-021-22241-w

The anatomy of past abrupt warmings recorded in Greenland ice

2021· article· en· W3151507768 on OpenAlexfundno aff
Émilie Capron, Sune Olander Rasmussen, Trevor Popp, Tobias Erhardt, Hubertus Fischer, Amaëlle Landais, Joel B Pedro, Guido Vettoretti, Aslak Grinsted, Vasileios Gkinis, Bruce H. Vaughn, Anders Svensson, Bo Vinther, James W. C. White

Bibliographic record

VenueNature Communications · 2021
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeology and Paleoclimatology Research
Canadian institutionsnot available
FundersNatural Environment Research CouncilNational Institute of Polar ResearchInstitut Polaire Français Paul Emile VictorCentre National de la Recherche ScientifiqueKorea Polar Research InstituteAgence Nationale de la RechercheNederlandse Organisatie voor Wetenschappelijk OnderzoekNatural Resources CanadaFonds Wetenschappelijk OnderzoekMinistry of Education, Culture, Sports, Science and TechnologyOffice of Polar ProgramsFonds De La Recherche Scientifique - FNRSSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungVillum FondenAustralian GovernmentEuropean CommissionUniversity of BernNational Science Foundation
KeywordsIce coreAbrupt climate changeClimatologyGeologyClimate stateClimate changeOceanographyGlobal warmingEffects of global warming

Abstract

fetched live from OpenAlex

Data availability and temporal resolution make it challenging to unravel the anatomy (duration and temporal phasing) of the Last Glacial abrupt climate changes. Here, we address these limitations by investigating the anatomy of abrupt changes using sub-decadal-scale records from Greenland ice cores. We highlight the absence of a systematic pattern in the anatomy of abrupt changes as recorded in different ice parameters. This diversity in the sequence of changes seen in ice-core data is also observed in climate parameters derived from numerical simulations which exhibit self-sustained abrupt variability arising from internal atmosphere-ice-ocean interactions. Our analysis of two ice cores shows that the diversity of abrupt warming transitions represents variability inherent to the climate system and not archive-specific noise. Our results hint that during these abrupt events, it may not be possible to infer statistically-robust leads and lags between the different components of the climate system because of their tight coupling.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.009
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.001
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 head0.022
GPT teacher head0.311
Teacher spread0.290 · 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 source (direct Gemma or distilled Codex), 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

Citations85
Published2021
Admission routes1
Has abstractyes

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