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Record W2064135016 · doi:10.1080/02786826.2014.896989

Effect of Induced Charge on Deposition of Uniformly Charged Particles in a Pediatric Oral-Extrathoracic Airway

2014· article· en· W2064135016 on OpenAlexaffabout
Mehdi Azhdarzadeh, Jason S. Olfert, Reinhard Vehring, Warren H. Finlay

Bibliographic record

VenueAerosol Science and Technology · 2014
Typearticle
Languageen
FieldMedicine
TopicInhalation and Respiratory Drug Delivery
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsDeposition (geology)DispersityParticle depositionRange (aeronautics)Reynolds numberParticle (ecology)Charged particleJet (fluid)MechanicsParticle sizeElectric chargeChemistryMaterials sciencePhysicsComposite materialIonPolymer chemistryPhysical chemistry

Abstract

fetched live from OpenAlex

An in vitro study was conducted in the Alberta idealized child mouth-throat, which mimics average deposition in a set of nine 6–14-year-old subjects, to examine the enhancement of deposition of monodisperse uniformly charged particles as a result of induced electrostatic forces. A purpose-based atomizer was designed and built for generating monodisperse, uniformly charged particles. The atomizer generates droplets by jet break up under the action of capillary waves and charges them via electrostatic induction. The experiments cover different particle aerodynamic diameters (d a = 3.6, 4.4, and 5.9 μm), at two flow rates (Q = 10 and 20 L/min), over a wide range of elementary charges per particle (0–10,000 e). The results show substantial increases in particle deposition in the present idealized pediatric mouth throat compared to neutral aerosols. Two empirical equations, as a function of Reynolds number, Stokes number, and induced charge number are introduced for the prediction of mouth-throat deposition in children, based on two different characteristic diameters of the airway.

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)0.001
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.062
Threshold uncertainty score0.220

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0000.000

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 head0.010
GPT teacher head0.277
Teacher spread0.267 · 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 designBench or experimental
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

Citations23
Published2014
Admission routes2
Has abstractyes

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