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Record W2067870553 · doi:10.1002/ppul.20767

Review of optimal characteristics of face‐masks for valved‐holding chambers (VHCs)

2008· review· en· W2067870553 on OpenAlex
Israel Amirav, Michael T. Newhouse

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

VenuePediatric Pulmonology · 2008
Typereview
Languageen
FieldMedicine
TopicInhalation and Respiratory Drug Delivery
Canadian institutionsMcMaster UniversitySt. Joseph’s Healthcare Hamilton
Fundersnot available
KeywordsMouthpieceMedicineInhalerFace masksMascaraIntensive care medicineBiomedical engineeringSurgeryDentistryAsthma

Abstract

fetched live from OpenAlex

Inhaled drugs are frequently given to infants and young children with a pressurized metered-dose inhaler (pMDI) attached to a valved-holding chamber (VHC) with face mask. In young children and infants who cannot breathe through a mouthpiece, the face mask serves as the interface between the patient and the VHC. Although the mask interface is one of the most important factors determining the dose of medication delivered from the VHC to the nose and mouth in these patients, its optimal characteristics are not well known. Recent studies clearly identify several face mask factors that determine the success or failure of drug delivery with these devices. This review summarizes the most important features of an optimal mask design such as: face seal/leak, volume of dead space, contour, flexibility, transparency, weight and cost. By optimizing these characteristics it should be possible to improve mask design. This will maximize the magnitude and reduce the variability of the dose presented to the respiratory tract while making the mask more comfortable and patient/caregiver-friendly.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.968
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
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 head0.059
GPT teacher head0.357
Teacher spread0.298 · 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