Comparison of impression techniques and double pouring by dental cast’s accuracy
Bibliographic record
Abstract
Aim: This study compared impression techniques and double pouring by means of cast’s accuracy. Methods: For each patient (n=10), impressions from right maxillary canine to first molar were made with acrylic resin trays and vinyl-polysiloxane using one single-step, and four two-steps techniques: relief with poly(vinyl chloride) film; tungsten-carbide bur/scalpel blade; small movements of the tray; non-relief. Total visible buccal surface area of crowns was measured three times using photographs from patients (Baseline) and casts. Mean area values (mm2) between Baseline and casts differences were analyzed by two-way repeated-measures ANOVA (α=.05; 1-β=85%). Results: No significant differences were observed for Impression Techniques (P=.525), Double Pouring (P=.281), and their interaction (P=.809). Conclusion: All impression techniques and double pouring produced casts with similar accuracy.
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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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".