Accuracy of Gypsum Casts after Different Impression Techniques and Double Pouring
Bibliographic record
Abstract
This study evaluated the accuracy of gypsum casts after different impression techniques and double pouring. Ten patients were selected and for each one it was obtained 5 partial putty/wash impressions with vinyl polysiloxane (VPS) material from teeth #13 to #16 with partial metal stock trays. The following techniques were performed: (1) one-step; two-step relief with: (2) PVC film; (3) slow-speed tungsten carbide bur and scalpel blade, (4) small movements of the tray and (5) without relief-negative control. The impressions were disinfected with 0.5% sodium hypochlorite for 10 minutes and stored during 110 and 230 minutes for the first and second pouring, respectively, with type IV gypsum. Three intra-oral lateral photographs of each patient were taken using a tripod and a customized radiographic positioner. The images were imported into ImageJ software and the total area of the buccal surface from teeth #13 to #16 was measured. A 4.0% coefficient of variance was criterion for using these measurements as Baseline values. The casts were photographed and analyzed using the same standardization for the clinical images. The area (mm2) obtained from the difference between the measurements of each gypsum cast and the Baseline value of the respective patient were calculated and analyzed by repeated-measures two way-ANOVA and Mauchly's Sphericity test (α = 0.05). No significant effect was observed for Impression technique (P = 0.23), Second pouring (P = 0.99) and their interaction (P = 0.25). The impression techniques and double pouring did not influence the accuracy of the gypsum casts.
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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".