Replication Data for: B.M. Crosland, M.R. Johnson, and E.A. Matida (2009) Characterization of the Spray Velocities from a Pressurized Metered-Dose Inhaler, Journal of Aerosol Medicine and Pulmonary Drug Delivery, 22(2):85-97 (doi: 10.1089/jamp.2008.0687).
Bibliographic record
Abstract
We have made detailed, spatially-resolved velocity measurements of the spray emitted from salbutamol sulfate pMDIs (pressurized metered dose inhalers) using particle image velocimetry (PIV). Instantaneous planar velocity measurements were taken and ensemble-averaged at various times during the spray event. The mean spray velocities were shown to be bimodal in time with two velocity peaks. Planar velocity data were analyzed to produce prescriptive velocity profiles suitable for use in numerical simulations. Statistical comparisons from several thousand spray events indicate that there is no significant difference in measured velocity between i) two brands of pMDI canisters, ii) two similar pMDIs from different lots, and iii) a full pMDI versus an almost-empty pMDI. Further experiments with a secondary air flow of 30 SLPM with and without an added cylindrical spacer deflected the spray downward, but had little effect on the velocity magnitude. The .xlsx file contains a summary of these results. Various worksheets contain the measured velocities, root-mean-squared variation of velocity, and curve-fit equations for the velocity in the x and y directions. All data are reported 1 mm downstream of the pMDI mouthpiece in a plane parallel to the exit plane.
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 | 0.007 | 0.136 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.005 | 0.010 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.726 | 0.452 |
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".