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Record W1536681237 · doi:10.1029/158gm15

Simulated History Of Convection in the Greenland and Labrador seas, 1948—2001

2005· book-chapter· en· W1536681237 on OpenAlexaboutno aff
Rüdiger Gerdes, J. Hurka, Michael Kärcher, Frank Kauker, Cornelia Köberle

Bibliographic record

VenueGeophysical monograph · 2005
Typebook-chapter
Languageen
FieldEarth and Planetary Sciences
TopicArctic and Antarctic ice dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsGeologyOceanographyConvectionClimatologyGroenlandiaGeophysicsGeographyMeteorologyIce sheet

Abstract

fetched live from OpenAlex

Convection in the Greenland and Labrador seas is compared using a sea-ice-ocean model forced with NCEP reanalysis atmospheric data for the period 1948-2001. Model-derived convection rates for the Greenland Sea and the Labrador Sea show good agreement with previous estimates. Composites based on convection indices are used to identify important forcing processes and the relationship to oceanic, atmospheric, and sea-ice fields. Convection in the Labrador Sea is dominated by large-scale atmospheric forcing, especially by the heat fluxes associated with the North Atlantic Oscillation (NAO). On the other hand, we find no robust correlation between Greenland Sea convection and the NAO. In the model, local sea-ice formation, wind direction, and associated sea-ice drift are important parameters affecting convection in the Greenland Sea.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.103
Threshold uncertainty score0.206

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 science0.0000.000
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 head0.012
GPT teacher head0.185
Teacher spread0.172 · 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 designSimulation or modeling
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

Citations25
Published2005
Admission routes1
Has abstractyes

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