LASER Sintered One-Piece Early-Loaded Dental Implants for Mandibular Premolars Replacement
Bibliographic record
Abstract
This study was designed to evaluate laser-sintered early-loaded 1-piece implants (OPI) based on clinical and radiographic findings. Thirty OPI were placed in the mandibular premolar area and subjected to early loading after 3 weeks of initial placement; patients were followed up for 6 months. Clinical evaluation included pocket depth, gingival health, implant stability, and esthetics. Periapical radiographs were used to measure the marginal bone loss (MBL). All implants were considered successful resulting in a survival rate of 100%. A remarkable difference (P < 0.01) existed when comparing MBL levels at 1 month with those at 3 and 6 months. Significant differences (P < 0.01) existed when comparing implant stability at 1 month to 3 months and at 3 months to 6 months. Moreover, significant differences (P < 0.01) were observed when comparing peri-implant probing depth at 1 month to that at 3 and 6 months on both the mesial and distal sides. The mean value of pink esthetic score was 11 at time of final restoration. The laser-treated early-loaded OPI design is associated with satisfactory clinical and radiographic follow-up results and it is a good alternative to the 2-piece design.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".