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Record W2124207940 · doi:10.5194/angeo-23-2433-2005

A new approach to momentum flux determinations using SKiYMET meteor radars

2005· article· en· W2124207940 on OpenAlexaff
W. K. Hocking

Bibliographic record

VenueAnnales Geophysicae · 2005
Typearticle
Languageen
FieldPhysics and Astronomy
TopicIonosphere and magnetosphere dynamics
Canadian institutionsWestern University
Fundersnot available
KeywordsMeteor (satellite)RadarGeologyMeteorologyForcing (mathematics)Momentum (technical analysis)Flux (metallurgy)Atmosphere (unit)Environmental scienceGravity waveAtmospheric sciencesGeophysicsRemote sensingGravitational wavePhysicsAerospace engineering

Abstract

fetched live from OpenAlex

Abstract. The current primary radar method for determination of atmospheric momentum fluxes relies on multiple beam studies, usually using oppositely directed coplanar beams. Generally VHF and MF radars are used, and meteor radars have never been successfully employed. In this paper we introduce a new procedure that can be used for determination of gravity wave fluxes down to time scales of 2-3h, using the SKiYMET meteor radars. The method avoids the need for beam forming, and allows simultaneous determination of the three components of the wind averaged over the radar volume, as well as the variance and flux components , where refers to the fluctuating eastward wind, refers to the fluctuating northward wind, and refers to the fluctuating vertical wind. Data from radars in New Mexico and Resolute Bay are used to illustrate the data quality, and demonstrate theoretically expected seasonal forcing. Keywords. Meteorology and atmospheric dynamics (Middle atmosphere dynamics; Waves and tides; Climatology)

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.001
Threshold uncertainty score0.003

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 communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
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 head0.014
GPT teacher head0.254
Teacher spread0.240 · 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

Citations138
Published2005
Admission routes1
Has abstractyes

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