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Record W2885496707 · doi:10.1029/2018gl078428

The Early Collapse of the 2017 Lincoln Sea Ice Arch in Response to Anomalous Sea Ice and Wind Forcing

2018· article· en· W2885496707 on OpenAlexafffund
G. W. K. Moore, Kaitlin McNeil

Bibliographic record

VenueGeophysical Research Letters · 2018
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicArctic and Antarctic ice dynamics
Canadian institutionsDairy Farmers of OntarioUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of CanadaUniversität BremenUniversity of WashingtonNational Center for Atmospheric Research
KeywordsSea iceArctic ice packGeologyClimatologyDrift iceOceanographyAntarctic sea iceArcticFast iceClimate changeArctic sea ice declineForcing (mathematics)

Abstract

fetched live from OpenAlex

Abstract One of the most dramatic indicators of climate change is the reduction in the extent and thickness of Arctic sea ice that has resulted in an increase in wind‐driven sea ice mobility. During April and May 2017, satellite observations indicated that the ice arch that forms between Nares Strait and the Lincoln Sea collapsed. Typically, this collapse occurs in July or August allowing multiyear ice to exit the Arctic through Nares Strait. Here we show that the period of the collapse was associated with the presence of a polynya in northern Nares Strait, thin ice in the Lincoln Sea, and an unusual wind regime characterized by strong northerly flow. We propose that these anomalous conditions resulted in the arch's early collapse. If the ice in the region continues to thin, early collapses may occur more frequently with implications for the regional as well as the downstream climate and ecosystems.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.016
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
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 head0.021
GPT teacher head0.281
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

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

Citations35
Published2018
Admission routes2
Has abstractyes

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