Effect of Implant Angulation, Connection Length, and Impression Material on the Dimensional Accuracy of Implant Impressions: An In Vitro Comparative Study
Bibliographic record
Abstract
BACKGROUND: With regard to implant-supported prostheses, to date no technique has been proven to guarantee a completely passive fit of prosthetic frameworks. Several clinical variables may affect the precision of impressions, particularly in the presence of implants. PURPOSE: To compare the accuracy of implant impressions made with different materials, lengths of impression coping connections, and not parallel position of the implants. MATERIALS AND METHODS: A calibrated testing device allowing reproducible standardized positions was used. Two control groups of master models and eight experimental groups with predetermined undercuts were used to make addition silicon and polyether implant impressions by means of the open-tray pick-up technique. Four reference distances were evaluated on each study cast by using a profile projector and a standardized measurement protocol. The data were statistically analyzed by means of three-factor analysis of variance. RESULTS: The impressions made in the presence of angulated implants were significantly less accurate than the ones made with parallel implants. The tested addition silicon resulted advantageous in presence of nonparallel implants whereas the polyether achieved the best results with parallel implants and standard impression copings. CONCLUSIONS: The angulation of the implants may cause strains of impressions, probably because of the higher forces required for the impression removal. Moreover, undercuts negatively affected the impression accuracy. More accurate casts were obtained using the tested addition silicon in the presence of nonparallel implants and using a standard length connection of the copings in the presence of parallel implants, respectively.
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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".