MétaCan
Menu
Back to cohort
Record W2043124476 · doi:10.1103/physrevlett.93.154503

Velocity Imaging of Highly Turbulent Gas Flow

2004· article· en· W2043124476 on OpenAlexaff
Benedict Newling, Christopher C. Poirier, Zhi Yang, James Rioux, Andrew J. Coristine, D. C. Roach, Bruce J. Balcom

Bibliographic record

VenuePhysical Review Letters · 2004
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Turbulent Flows
Canadian institutionsUniversity of New Brunswick
Fundersnot available
KeywordsTurbulenceMechanicsReynolds numberPhysicsPointwiseComputational fluid dynamicsBluffWind tunnelFluid dynamicsStall (fluid mechanics)Mathematics

Abstract

fetched live from OpenAlex

We introduce a noninvasive, quantitative magnetic resonance imaging (MRI) wind-tunnel measurement in flowing gas (>10 m s(-1)) at high Reynolds numbers (Re>10(5)). The method pertains to liquids and gases, is inherently three dimensional, and extends the range of Re to which MRI is applicable by orders of magnitude. There is potential for clear time savings over traditional pointwise techniques. The mean velocity and turbulent diffusivity of gas flowing past a bluff obstruction and a wing section at realistic stall speeds were measured. The MRI data are compared with computational fluid dynamics.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.080
Threshold uncertainty score0.591

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.006
GPT teacher head0.219
Teacher spread0.213 · 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 teacher head, 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

Citations80
Published2004
Admission routes1
Has abstractyes

Explore more

Same venuePhysical Review LettersSame topicFluid Dynamics and Turbulent FlowsFrench-language works237,207