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Record W3181703224 · doi:10.1089/jamp.2021.29040.whf

Deposition of Aerosols in the Lungs: Particle Characteristics

2021· review· en· W3181703224 on OpenAlex

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 Aerosol Medicine and Pulmonary Drug Delivery · 2021
Typereview
Languageen
FieldMedicine
TopicInhalation and Respiratory Drug Delivery
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsParticle depositionDeposition (geology)Particle (ecology)Materials scienceChemical physicsParticle sizeVolatility (finance)ChemistryNanotechnologyMechanicsPhysicsComposite materialRange (aeronautics)Geology

Abstract

fetched live from OpenAlex

Of the various particle properties that affect deposition in the respiratory tract, particle diameter and particle density are the most commonly considered, since their effect on deposition is well known and important, as has been discussed earlier in this chapter. However, there are several other particle properties that can affect particle deposition in the lungs. These include: 1) electrostatic charge on the particle, which can cause electrostatic forces to enhance deposition; 2) the shape of the particle, which can cause its trajectory to differ from that of a spherical particle and thereby alter its deposition; and 3) volatility of the particle i.e., its ability to condense or evaporate at its surface, which can change its diameter and in turn affect its deposition. In this section, we examine each of these three factors individually.

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: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.953
Threshold uncertainty score0.760

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
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 head0.045
GPT teacher head0.323
Teacher spread0.278 · 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