Fresh‐Socket Implants of Different Collar Length: Clinical Evaluation in the Aesthetic Zone
Bibliographic record
Abstract
BACKGROUND: The aim of this clinical study was to compare clinical evaluations of implants in the aesthetic zone with smooth collars of different length. MATERIALS AND METHODS: Sixty-six patients requiring extractions of one, two, or three teeth in the aesthetic zone of the maxilla were enrolled in this study. Ninety-four implants were positioned and were loaded immediately after tooth extraction. Forty-seven implants with a short smooth collar of 0.5 mm (SCI) and 47 implants with a long smooth collar of 1.8 mm (LCI) were utilized in this study and were placed using a nonsubmerged approach. Clinical (gingival index, modified plaque index, modified bleeding index, probing depth, gingival recession) and intraoral digital radiographic parameters were measured at baseline and after 6, 12, 24, and 36 months of healing to evaluate crestal bone loss levels over time. RESULTS: After a follow-up period of 36 months, a survival rate of 100% was reported. The SCI group showed a mean bone loss of 1.07 ± 0.38 mm at 12 months and 1.09 ± 0.38 mm at 36 months. The LCI group showed a mean bone loss of 0.46 ± 0.14 mm at 12 months and 0.53 ± 0.12 mm at 36 months. After the 36-month follow-up period, both groups showed stable bone levels over time. Statistically significant differences were found between groups (p < .05). No statistically significant differences were found between SCI and LCI groups with regard to clinical parameters over time. CONCLUSIONS: This study revealed significant differences in radiographically observed marginal bone loss between the two types of implant with different smooth-collar lengths, but no differences in gingival vestibular margin outcome were observed.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".