Comparison of Two Approaches for Treating Cascade Impaction Mass Balance Measurements
Why this work is in the frame
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Bibliographic record
Abstract
The multistage cascade impactor (CI) is the most appropriate tool for measuring the aero-dynamic particle size distribution (APSD) of active pharmaceutical ingredient(s) (API) in the aerosol from an orally inhaled drug product. It is possible to determine the total emitted mass per actuation of the inhaler by summing the individual component results obtained when determining APSD. The determination of total mass per actuation recovered from the CI components (or "mass balance" [MB]) has inherently lower precision than that of a delivered dose (DD) determination. An FDA draft guidance for industry has proposed using CI-determined MB as part of the product specification, with acceptance criteria of +/-15% of the label claim (LC) dosage. We propose instead that MB be used to assess whether the CI measurement of APSD is reliable. Two multitiered test schemes for MB are evaluated that allow for retests to accommodate the variability of the MB measurement. We provide statistical evaluations of both test schemes by using operating characteristic (OC) curves. We find that a two-tiered procedure with broader acceptance criteria but limited opportunity for investigating and retesting MB failure results in a greater risk of rejection of good batches ("false positive" error) without the commensurate reduction in the risk of passing unacceptable batches ("false negative" error). In contrast, a three-tiered procedure with narrower acceptance criteria, but more opportunity to check for potential CI system malfunction/method misapplication and to rerun the CI test, provides a compromise that enables the MB measurement to be used without significantly increasing the probability of false positive errors.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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