Recent Advances in Predictive Understanding of Respiratory Tract Deposition
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.
Bibliographic record
Abstract
Accurate prediction of respiratory tract deposition is important in gauging the health risks of ambient bioaerosols and environmental aerosols, as well as in developing pharmaceutical aerosols for drug delivery. The present article highlights recent advances in the prediction of total, extrathoracic, and lung deposition fractions of inhaled aerosols over a broad range of parameters for both oral and nasal breathing. These advances build on recent data from in vivo and in vitro studies that have benefited from recent improvements in high-resolution imaging, rapid prototyping, and computational simulation abilities that have significantly enhanced the current understanding of respiratory tract deposition. It is anticipated that the relatively simple equations for predicting total or whole lung deposition that follow from the recent work discussed herein will allow for improved correlation between respiratory tract deposition and a wide range of health outcomes.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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