Clinical Evaluation of the NobelActive Implant System: A Case Series of 107 Consecutively Placed Implants and a Review of the Implant Features
Bibliographic record
Abstract
The purpose of this paper is to (1) introduce the features of this new implant, (2) investigate the clinical benefits as advertised by the manufacturer in comparison with traditional root form implants, and (3) provide guidelines for its use. One hundred seven NobelActive implants were placed in 67 consecutive patients with type I-IV bone within 8 months. Cases also include implants placed in sinus grafts, ridges with insufficient thickness and facial bone loss and were placed with delayed and immediate loading. Parameters were assessed to determine whether we could confirm the manufacturer's statements on this implant system. Results obtained with 107 implants of 3.5, 4.3, and 5 mm diameters with 10- to 15-mm lengths placed in different types of bone with delayed and immediate loading demonstrated a final insertion torque from 15 to 70 Ncm. All types of bone allowed "redirection" of the implant but were limited in the bone with higher density. According to the manufacturer, this new design of the NobelActive implant has high initial stability, bone condensing properties, redirecting capability, built-in platform shifting, and dual-function prosthetic connections. After investigating these 5 statements within the limits of our study, we were able to confirm these claims, but with some recommendations for the clinical use and placement of these implants.
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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 | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".