MétaCan
Menu
Back to cohort
Record W4382243924 · doi:10.1080/02786826.2023.2228378

Measurement of the centrifugal particle mass analyzer transfer function

2023· article· en· W4382243924 on OpenAlexaff
Arash Naseri, Tyler J. Johnson, Gregory J. Smallwood, Jason S. Olfert

Bibliographic record

VenueAerosol Science and Technology · 2023
Typearticle
Languageen
FieldEngineering
TopicCyclone Separators and Fluid Dynamics
Canadian institutionsNational Research Council CanadaUniversity of Alberta
Fundersnot available
KeywordsChemistryMass transferRange (aeronautics)Particle (ecology)Materials scienceChromatography

Abstract

fetched live from OpenAlex

Particle mass analyzers, in particular the centrifugal particle mass analyzer (CPMA) and the aerosol particle mass analyzer (APM), have provided new possibilities for aerosol science through their ability to classify particles by their mass-to-charge ratio. The performance of the CPMA in classifying particles is characterized by a probability distribution known as a transfer function. This study shows the theoretical models of the CPMA’s transfer function that exist in the literature cannot accurately predict the CPMA’s actual performance. In this study, a tandem CPMA (TCPMA) measurement technique was used to experimentally evaluate the deviation of the actual CPMA transfer function from its idealized triangular transfer function. This deviation was measured by three factors: (i) the width factor (μ), (ii) the height factor (η), and (iii) the mass set point agreement (i.e., the agreement between the set points of the two CPMAs, m12∗); such that concurrent values of 1 for all three factors implied no deviation between the actual and theoretical triangular CPMA transfer functions. These factors were derived by adjusting them to fit TCPMA data with the convolution of two triangular transfer functions with identical widths. TCPMA data were collected for a wide range of CPMA resolutions, flow rates, and mass set points ranging from 2 to 15, 0.3 to 8 LPM, and 0.05 to 100 fg, respectively. The mass set point agreement remained relatively constant over a range of CPMA mass set points and increased slightly with decreasing CPMA resolutions. Neglecting outliers, the average mass set point agreement was m12∗=1.02±0.03, suggesting good reproducibility among the CPMAs. The width factor showed a functional dependence on the mass set point, resolution, and flow rate. It was observed that the CPMA transfer function was generally narrower (μ>1) than the idealized transfer function except at a low flow rate (0.3 LPM) and low mass set points (m∗<1 fg), and the width factor approached unity at higher mass set points (m∗>1 fg) and higher resolutions (Rm>6). As expected, the height factor depends on the mass set point, resolution, and flow rate: it decreases with lower mass set points, lower flow rates and higher resolutions. Both the width and height factors were fitted robustly using multivariate non-linear fitting models so that CPMA users can easily calculate its transfer function over a wide range of operating conditions.Copyright © 2023 American Association for Aerosol Research

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)0.004
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.004
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.011
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.008
GPT teacher head0.191
Teacher spread0.183 · 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 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

Citations13
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueAerosol Science and TechnologySame topicCyclone Separators and Fluid DynamicsFrench-language works237,207