Initial development of a variable-friction floor surface
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
Efficient delivery of dry powder aerosols dispersed with low volumes of air is challenging. This study aims to develop an efficient dry powder inhaler (DPI) capable of delivering spray-dried Survanta-EEG powders (3-10 mg) with a low volume (3 mL) of dispersion air. A series of iterative design modifications were made to a base low air volume actuated DPI. The modifications included the replacement of the original capsule chamber with an integral dose containment chamber, alteration of the entrainment air flow path through the device (from single-sided (SS) to straight through (ST)), change in the number of air inlet holes (from one to three), varying the outlet delivery tube length (45, 55, and 90 mm) and internal diameter (0.60, 0.89, and 1.17 mm). The modified devices were evaluated by determining the influence of the modifications and powder fill mass on aerosol performance of spray-dried Survanta-EEG powders. The optimal DPI was also evaluated for its ability to aerosolize a micronized powder. The optimized dose containment unit DPI had a 0.21 mL powder chamber, ST airflow path, three-0.60 mm air inlet holes, and 90 mm outlet delivery tube with 0.89 mm internal diameter. The powder dispersion characteristics of the optimal device were independent of fill mass with good powder emptying in one 3 mL actuation. At 10 mg fill mass, this device had an emitted mass of 5.3 mg with an aerosol Dv50 of 2.7 μm. After three 3 mL actuations, >85% of the spray-dried powder was emitted from the device. The emitted mass of the optimal device with micronized albuterol sulfate was >72% of the nominal fill mass of 10 mg in one 3 mL actuation. Design optimization produced a DPI capable of efficient performance with a dispersion air volume of 3 mL to aerosolize Survanta-EEG powders.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.001 | 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