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Record W1989238306 · doi:10.1029/2008jc004859

Mean surface topography of the northwest Atlantic: Comparison of estimates based on satellite, terrestrial gravity, and oceanographic observations

2009· article· en· W1989238306 on OpenAlexaff
Keith R. Thompson, Jianliang Huang, M. Véronneau, Daniel G. Wright, Youyu Lu

Bibliographic record

VenueJournal of Geophysical Research Atmospheres · 2009
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeophysics and Gravity Measurements
Canadian institutionsMEG-3 (Canada)Bedford Institute of OceanographyEnvironment and Climate Change CanadaFisheries and Oceans CanadaGeological Survey of CanadaNatural Resources CanadaDalhousie University
Fundersnot available
KeywordsAltimeterGeologyGeoidOcean currentSea-surface heightOcean surface topographySea surface temperatureGeodesySurface gravityOceanographyGulf StreamClimatologyGeophysicsPhysicsMeasured depth

Abstract

fetched live from OpenAlex

The accuracy of a new mean sea surface topography (MSST) of the northwest Atlantic is assessed. The MSST is estimated from 12 years of altimeter observations referenced with respect to a new regional geoid based on a blend of Gravity Recovery and Climate Experiment (GRACE), terrestrial, and altimeter‐derived gravity data. The new MSST is first compared to a recently published mean surface topography calculated using an eddy‐permitting model of the North Atlantic. Geostropic currents calculated from the GRACE‐based MSST are next compared to mean surface currents in the northwest Atlantic estimated from the motion of near‐surface drifters corrected for surface Ekman effects. Finally, the mean path of the Gulf Stream is compared to the line of zero skewness of sea level variability which provides a measure of the mean path of unstable, intense ocean currents. Overall the agreement amongst the various estimates of surface topography and circulation is excellent. There are, however, some significant differences that can be separately attributed to problems with the MSST and, in some cases, with the ocean model (in particular the ocean climatology to which it was nudged).

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)0.000
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 score0.009
Threshold uncertainty score0.630

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0000.000

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 head0.069
GPT teacher head0.315
Teacher spread0.246 · 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

Citations19
Published2009
Admission routes1
Has abstractyes

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