Poster - Thur Eve - 68: Assessment of post-fabrication deformation in three styles of thermoplastic masks
Bibliographic record
Abstract
This work assesses the post fabrication shrinkage of 3 styles of Aquaplast Slimline U-Frame thermoplastic masks: Aquaplast RT (Aqua S); Fibreplast (Aqua KS) which is similar to Aqua S, but contains Kevlar for improved rigidity and reduced shrinkage; and Aquaplast RT Variable Perf (Aqua YS) which is similar to Aqua S but excludes perforations along various bands for improved strength. Each mask was formed over the same rigid anthropomorphic head phantom. Immediately post-fabrication, each mask was remounted onto an optical bench, where sequences of profile photographs were acquired over the span of one week. Points marked near the forehead, nose, and chin were tracked to determine the deformation of the masks. Reproducibility of point position determination was within about 0.02 mm. After one week, all points translated primarily in the posterior direction due to mask shrinkage. Observed translations were largest for the Aqua S mask where points translated by 2.31±0.05mm on average. The Aqua YS mask yielded the smallest translations: 1.57±0.03mm, 1.20±0.03mm, and 1.54±0.03mm for points near the forehead, nose and chin respectively. The Aqua KS mask yielded somewhat greater translations: 1.57±0.02mm, 1.20±0.02mm and 1.54±0.02mm for the same respective points. Future work will characterize other mask models and measure the pressure exerted at select points by each mask on the phantom after shrinkage.
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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 | 0.000 | 0.001 |
| 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) | 0.003 | 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 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".