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Record W2011617634 · doi:10.1029/2000jc000578

Analysis of velocity field in the eastern Black Sea from satellite data during the Black Sea '99 experiment

2002· article· en· W2011617634 on OpenAlexaff
Y. D. Afanasyev, Andrey G. Kostianoy, А. Г. Зацепин, Pierre‐Marie Poulain

Bibliographic record

VenueJournal of Geophysical Research Atmospheres · 2002
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicMarine and environmental studies
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsGeologyMesoscale meteorologySatelliteGeostrophic currentBlack seaSea surface temperatureAdvanced very-high-resolution radiometerOcean colorSeaWiFSEddyVorticityOcean surface topographyOcean currentClimatologyRemote sensingOceanographyMeteorologyVortexGeographyTurbulencePhysics

Abstract

fetched live from OpenAlex

Maximum cross correlation (MCC) analysis of National Oceanic and Atmospheric Administration (NOAA) advanced very high resolution radiometer (AVHRR) imagery of the eastern Black Sea in late September 1999 has been used to reconstruct the velocity and vorticity fields of the upper layer of the sea. Analysis revealed the large‐scale dynamic features characteristic of the Black Sea, namely the Rim Current, as well as the detailed pattern of mesoscale vortical activity including meanders, eddies, and dipoles, which are often observed on satellite visible, infrared, or sea color imagery. The dynamical character of the pronounced dipole structure in the northeastern part of the Black Sea was determined by comparison with satellite IR images, geostrophic velocities calculated on the basis of conductivity‐temperature‐depth (CTD) casts performed and trajectories of six Argos‐tracked surface velocity program (SVP) drifters deployed during the Black Sea '99 expedition onboard R/V Akvanavt on 25–30 September 1999.

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 score0.050
Threshold uncertainty score0.100

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.299
Teacher spread0.230 · 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

Citations38
Published2002
Admission routes1
Has abstractyes

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