MétaCan
Menu
Back to cohort
Record W2022527223 · doi:10.1089/jamp.2011.0897

Using MRI to Measure Aerosol Deposition

2012· review· en· W2022527223 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 · 2012
Typereview
Languageen
FieldPhysics and Astronomy
TopicAtomic and Subatomic Physics Research
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsAerosolDeposition (geology)Magnetic resonance imagingHuman lungEnvironmental scienceBiomedical engineeringChemistryLungMedicineRadiologyGeologyInternal medicine

Abstract

fetched live from OpenAlex

This article provides a concise review of the use of magnetic resonance imaging (MRI) for measurement of regional aerosol deposition in the lungs. Basic aspects of MRI and its use in lung imaging and measurement of regional ventilation are introduced. Imaging of hydrogen protons (water) and inhaled hyperpolarized gases as the MRI source signals are discussed. The addition of contrast agents to aerosol particles in order to allow measurement of regional aerosol deposition is considered. Existing in vitro human and in vivo animal model measurements of regional aerosol deposition in the respiratory tract demonstrate the capability of MRI in this regard. However, as a tool for human deposition studies, current approaches require contrast agent doses that are too high to be considered competitive with traditional radionuclide aerosol deposition measurement methods. Thus, future use of MRI in human studies of regional aerosol deposition is predicated on improvement over present approaches.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.990
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
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 head0.090
GPT teacher head0.349
Teacher spread0.259 · 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