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Record W2521927654 · doi:10.1002/2016gl070454

Wind‐driven mixing at intermediate depths in an ice‐free Arctic Ocean

2016· article· en· W2521927654 on OpenAlexaffabout
Ben Lincoln, Tom P. Rippeth, Yueng‐Djern Lenn, Mary Louise Timmermans, William J. Williams, Sheldon Bacon

Bibliographic record

VenueGeophysical Research Letters · 2016
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicArctic and Antarctic ice dynamics
Canadian institutionsFisheries and Oceans Canada
FundersNatural Environment Research CouncilSight Research UK
KeywordsDrift iceSea iceArctic ice packGeologyArctic sea ice declineArcticAntarctic sea iceOceanographyStratification (seeds)ClimatologyCryosphereCanada BasinAtmospheric sciences

Abstract

fetched live from OpenAlex

Abstract Recent seasonal Arctic Ocean sea ice retreat is a major indicator of polar climate change. The Arctic Ocean is generally quiescent with the interior basins characterized by low levels of turbulent mixing at intermediate depths. In contrast, under conditions of reduced sea ice cover, there is evidence of energetic internal waves that have been attributed to increased momentum transfer from the atmosphere to the ocean. New measurements made in the Canada Basin during the unusually ice‐free and stormy summer of 2012 show previously observed enhancement of internal wave energy associated with ice‐free conditions. However, there is no enhancement of mixing at intermediate depths away from significant topography. This implies that contrary to expectations of increased wind‐induced mixing under declining Arctic sea ice cover, the stratification in the central Canada Basin continues to suppress turbulent mixing at intermediate depths and to effectively isolate the large Atlantic and Pacific heat reservoirs from the sea surface.

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)0.000
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 score0.028
Threshold uncertainty score0.055

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
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 head0.025
GPT teacher head0.273
Teacher spread0.248 · 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

Citations63
Published2016
Admission routes2
Has abstractyes

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