MétaCan
Menu
Back to cohort
Record W7106028996 · doi:10.24400/527896/a03-2014.3175

Spatial Variations of the Near-Uniform Sea Level and Ocean Bottom Pressure Fluctuation Identified in the Arctic Mediterranean

2014· article· W7106028996 on OpenAlexaboutno aff

Bibliographic record

VenueCentre National d’Etudes Spatiales · 2014
Typearticle
Language
FieldEarth and Planetary Sciences
TopicOceanographic and Atmospheric Processes
Canadian institutionsnot available
Fundersnot available
KeywordsArcticArctic dipole anomalyForcing (mathematics)Canada BasinOceanic basinContinental shelfOcean surface topographyDeep seaMediterranean seaOcean dynamics

Abstract

fetched live from OpenAlex

The nature of near-uniform fluctuations of sea level and ocean bottom pressure found across the deep ocean basins of the Arctic Ocean and the Nordic Seas is revisited. Here, we focus on the fluctuations' spatial variation. Previous investigations have identified the principal cause of the fluctuation being winds along the continental slopes forcing divergent coastally trapped waves. Using an ocean general circulation model and its adjoint, the spatial variation of this mechanism is further examined, including differences across the Arctic Mediterranean and discrepancies between contributions from within and outside the domain (e.g., Figure below). Mechanisms underlying the fluctuation's difference between the deep ocean basins and the shallow coastal regions will also be discussed and the fluctuation's far-field response examined. The fast barotropic process accounts for most of the sub-monthly to interannual variations of sea level and ocean bottom pressure in the deep Arctic basins. Figure Caption: Sensitivity of mean ocean bottom pressure across the deep ocean basins of the Arctic Mediterranean to winds along- (A) and across-bathymetry (B). Note the dominance of (A) over (B), differences in sign between those within and outside the Arctic region in (A), and variations along the continental slopes especially regions with weak sensitivity.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.210
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.020
GPT teacher head0.221
Teacher spread0.201 · 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

Citations0
Published2014
Admission routes1
Has abstractyes

Explore more

Same venueCentre National d’Etudes SpatialesSame topicOceanographic and Atmospheric ProcessesFrench-language works237,207