Next Generation Pharmaceutical Impactor (A New Impactor for Pharmaceutical Inhaler Testing). Part II: Archival Calibration
Bibliographic record
Abstract
A new seven-stage cascade impactor, the Next Generation Pharmaceutical Impactor (NGI), has been developed for the pharmaceutical industry. A calibration following "good laboratory practice (GLP)" procedures has been performed on a specific archival NGI, deemed to be representative of all NGIs. Thus, this impactor had nozzle dimensions for each stage manufactured close to the middle of the tolerance band for the design specification, and therefore the average nozzle diameter was equal to the nominal value for that stage. An essential feature of the NGI is that it is designed to operate at any flow rate between 30 and 100 L/min. Thus, the calibration was made at inlet flow rates of 30, 60 and 100 L/min representing the lower bound, mid-region and upper bound of the specified range of operation for the impactor. The calibration data were then used to develop equations that predict the particle cut size for all components of the impactor at any flow rate from 30 to 100 L/min.
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.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.003 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".