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Record W1980809271 · doi:10.1175/2007jamc1319.1

Along-Valley Structure of Daytime Thermally Driven Flows in the Wipp Valley

2008· article· en· W1980809271 on OpenAlexafffund
Magdalena Rucker, Robert M. Banta, D. G. Steyn

Bibliographic record

VenueJournal of Applied Meteorology and Climatology · 2008
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicCryospheric studies and observations
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of CanadaNational Oceanic and Atmospheric AdministrationCanadian Foundation for Climate and Atmospheric Sciences
KeywordsMesoscale meteorologyDaytimeGeologyRiver valleyPressure gradientAccelerationFlow (mathematics)LidarAdvectionGeomorphologyAtmospheric sciencesClimatologyGeographyGeometryRemote sensingOceanography

Abstract

fetched live from OpenAlex

Abstract High-resolution Doppler lidar observations obtained during the Mesoscale Alpine Program (MAP) 1999 field campaign are used to investigate the along-valley structure of daytime valley flows in the Wipp Valley, Austria. The observations show that under varying ambient conditions the valley flow increases in speed through a narrow section of the valley. Furthermore, the along-valley volume flux diverges along the valley segment under investigation, which suggests that the observed along-valley acceleration of the valley flow cannot be explained by the horizontal constriction of the valley sidewalls. It is hypothesized that the along-valley acceleration of the flow is caused by an intravalley change in the horizontal pressure gradient induced by differential heating rates of the valley atmosphere.

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)0.000
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 score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.014
GPT teacher head0.214
Teacher spread0.199 · 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

Citations30
Published2008
Admission routes2
Has abstractyes

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