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Record W3112993248 · doi:10.1089/jamp.2021.29033.am

Regional Deposition: Targeting

2020· article· en· W3112993248 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 · 2020
Typearticle
Languageen
FieldMedicine
TopicInhalation and Respiratory Drug Delivery
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsAerosolDeposition (geology)InhalationAerodynamic diameterRespiratory tractExhalationEnvironmental scienceNanotechnologyMedicineMeteorologyRespiratory systemMaterials scienceBiologyPhysicsInternal medicineAnesthesia

Abstract

fetched live from OpenAlex

Patterns of regional aerosol deposition within the lungs are known to vary in a predictable manner with a number of factors, most notably aerodynamic particle size and inhalation pattern. Targeting deposition involves the intentional manipulation of one or more of these factors to promote aerosol deposition in certain locations within the respiratory tract. This section will begin by exploring existing evidence supporting the need to target regional deposition. Thereafter, various approaches to targeting will be introduced. In addition to control of aerodynamic particle size and inhalation pattern, a collection of approaches are available through which to passively target deposition to more central or peripheral lung regions. These include the delivery of short aerosol boluses at prescribed time points in inhalation, control of transient hygroscopic aerosol size changes during transport through the respiratory tract, and use of alternative carrier gas mixtures such as helium/oxygen mixtures. Comparatively, targeting aerosol deposition locally to very precise, spatially-defined lung regions is in its infancy. Early, exploratory techniques used for local targeting will be described. The continued evolution of deposition targeting towards ever more specific locations within the lungs is required to explore fundamental research questions in aerosol medicine: namely, how precise does targeting need to be before additional refinement fails to produce appreciably different therapeutic effects, and which nascent applications of aerosols in medicine might benefit from more selective regional targeting?

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)0.000
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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.191
Threshold uncertainty score0.526

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 head0.031
GPT teacher head0.262
Teacher spread0.230 · 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