MétaCan
Menu
Back to cohort
Record W2072906484 · doi:10.1029/2001jd002049

Lagrangian simulation of suspended particles in the neutrally stratified surface boundary layer

2002· article· en· W2072906484 on OpenAlex
Peter A. Taylor, P. Y. Li, John D. Wilson

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Geophysical Research Atmospheres · 2002
Typearticle
Languageen
FieldEngineering
TopicParticle Dynamics in Fluid Flows
Canadian institutionsUniversity of AlbertaYork University
Fundersnot available
KeywordsSettlingMechanicsBoundary layerPhysicsParticle (ecology)TurbulenceMagnetosphere particle motionEddy diffusionClassical mechanicsTurbulent diffusionGeologyThermodynamics

Abstract

fetched live from OpenAlex

The one‐dimensional equation of motion for suspended particles in the neutral atmospheric surface boundary layer is solved for the particle motion assuming that the sequence of vertical fluid velocities at the (moving) particle location can be modeled by a generalized Langevin equation. This inertial particle model is used to produce concentration profiles above a reflecting lower boundary for neutrally buoyant particles with inertia and for heavy particles with gravitational settling. Near the ground, modeled particle number concentration profiles above an infinite plane depart from the standard power law solution predicted by diffusion models. We investigate effective settling velocity and the eddy diffusivity for particles in this turbulent boundary layer flow and find that, near the ground, both are reduced in relation to particle terminal velocity and the assumptions made in boundary layer diffusion models.

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.

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)0.001
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 score0.084
Threshold uncertainty score0.332

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.061
GPT teacher head0.330
Teacher spread0.270 · 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