Short Implants: A Descriptive Study of 273 Implants
Bibliographic record
Abstract
PURPOSE: The study aims to assess the performance of short implants in a series of patients with severe alveolar resorption. MATERIALS AND METHODS: A review is made of 273 implants measuring 10 mm or less, placed by conventional surgery or using osteotomes, and with a postloading follow-up of between 18 months and 12 years (mean 81 months). RESULTS: A total of 20 failures were recorded (7.33%), with a global implant survival of 92.67%. The survival rate for 10 mm implants was 92.82%, versus 92.5% in the case of those measuring less than 10 mm. Overall, the failure rate was lowest for the treated surface implants (2.56% vs 4.76%). On considering the implants measuring under 10 mm, the failure rates were similar in both groups (3.77%). CONCLUSIONS: Short implants are a good treatment alternative for patients with severe alveolar resorption of both jaws.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".