MétaCan
Menu
Back to cohort
Record W2165275603 · doi:10.1175/2008jas2814.1

How Generic Are Dipolar Jet EOFs?

2008· article· en· W2165275603 on OpenAlexafffund
Adam H. Monahan, John C. Fyfe

Bibliographic record

VenueJournal of the Atmospheric Sciences · 2008
Typearticle
Languageen
FieldEnvironmental Science
TopicClimate variability and models
Canadian institutionsUniversity of VictoriaCanadian Institute for Advanced Research
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institute for Advanced Research
KeywordsJet (fluid)Position (finance)SkewnessPhysicsDipoleExtratropical cycloneStatistical physicsComputational physicsMechanicsAtmospheric sciencesQuantum mechanicsMathematics

Abstract

fetched live from OpenAlex

Abstract Dipolar structures arise as empirical orthogonal functions (EOFs) of extratropical tropospheric zonal-mean zonal wind in observations, in idealized dynamical models, and in complex general circulation models. This study characterizes the conditions under which dipoles emerge as EOFs of a jet of fixed shape f (x), which takes a unique localized extremum and is smooth but is otherwise arbitrary, characterized by fluctuations in strength, position, and width of arbitrary distribution. It is shown that the factors that influence the extent to which a dipolelike structure will arise as an EOF are (i) the skewness of position fluctuations, (ii) the dependence of position fluctuations on strength and width fluctuations, and (iii) the relative strength of the position and width fluctuations. In particular, the leading EOF will be a dipole if jet position fluctuations are not strongly skewed, not strongly dependent on strength and width fluctuations, and sufficiently large relative to strength and width fluctuations. Because these conditions are generally satisfied to a good approximation by observed and simulated tropospheric eddy-driven jets, this analysis provides a simple explanation of the ubiquity of dipolar jet EOFs.

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)0.002
metaresearch head score (Gemma)0.013
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0020.003
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.037
GPT teacher head0.225
Teacher spread0.189 · 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

Citations4
Published2008
Admission routes2
Has abstractyes

Explore more

Same venueJournal of the Atmospheric SciencesSame topicClimate variability and modelsFrench-language works237,207