Appropriate Face Models for Evaluating Drug Delivery in the Laboratory: The Current Situation and Prospects for Future Advances
Why this work is in the frame
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Bibliographic record
Abstract
The laboratory evaluation of inhalers with facemasks for patient interface is so complex that testing without a facemask is generally undertaken, a practice that has been advocated in one standard. However, the facemask itself can profoundly influence medication delivery. A systematic review of the literature was undertaken to establish the development history of face models for the evaluation of facemasks used with inhalers and accessories. Initial attempts to simulate the facemask-face boundary employed a circular, firm rubber flange plate upon which the facemask was located. However, such models did not represent dead volume accurately, which is particularly important when assessing infant use. Subsequent developments included the creation of more realistic facial features, enabling the aerosol leaving the inhaler to be quantified at the facemask. In one instance (SAINT model), an anatomically correct nasopharyngeal cavity has been combined with a model face, enabling assessment of medication delivery to be extended to the lower respiratory tract. However, it is necessary either to apply sealants or to compress the facemask beyond normal to eliminate leakage with the rigid facial structure that is incomplete above the bridge of the nose. An oral-breathing infant full-face model (ADAM) intended to be used to quantify emitted mass at the patient interface incorporates flexible facial features to overcome this limitation. There is a need to extend the flexible face approach to other models that may be developed in the future for testing facemasks, whether or not they incorporate anatomically correct realizations of the upper respiratory tract.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it