MétaCan
Menu
Back to cohort
Record W4394816768 · doi:10.31857/s2686739722602824

FORMATION OF WINTER SURFACE TEMPERATURE ANOMALIES IN THE NORTH ATLANTIC IN DECADES OF NEGATIVE AND POSITIVE VALUES OF THE NORTH ATLANTIC OSCILLATION INDEX

2023· article· en· W4394816768 on OpenAlexaboutno aff
А. А. Сизов, T. M. Bayankina, V. L. Pososhkov

Bibliographic record

VenueДоклады РОССИЙСКОЙ АКАДЕМИИ НАУК Науки о Земле · 2023
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicArctic and Antarctic ice dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsNorth Atlantic oscillationAtlantic multidecadal oscillationGulf StreamAnomaly (physics)PeninsulaOceanographyGeologyNorth Atlantic Deep WaterAnticycloneClimatologyAtlantic Equatorial modeSea surface temperatureThermohaline circulationGeography

Abstract

fetched live from OpenAlex

An analysis of the variability of the winter surface temperature anomaly in the North Atlantic in decades of negative and positive values of the North Atlantic Oscillation Index is presented. It was found that in the decade with negative values of the North Atlantic Oscillation Index, the slope waters of the Gulf Stream system and Labrador Current waters decrease the temperature of the Gulf Stream at the mixing zone on the Scotia Peninsula shelf and in the area of the quasistationary anticyclonic vortex to a maximum. In the decade with positive values of the North Atlantic Oscillation Index, the temperature of the slope waters is close to the climate. Taking into account the increased speed of the Gulf Stream in the years with positive values of the North Atlantic Oscillation Index, the spreading of the surface ocean temperature anomaly over the North Atlantic water area occurs for a shorter time than in the years with its negative values.

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 score0.004
Threshold uncertainty score0.008

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)0.0010.000

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 head0.008
GPT teacher head0.206
Teacher spread0.198 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueДоклады РОССИЙСКОЙ АКАДЕМИИ НАУК Науки о ЗемлеSame topicArctic and Antarctic ice dynamicsFrench-language works237,207