RETRACTED: Influence of diameter and length on primary stability in various implant site densities—An in vitro study in polyurethane blocks
Post-publication record
OpenAlex flags this work as retracted, but it carries no matching Retraction Watch record in this frame.
Bibliographic record
Abstract
Abstract Background The influence of dental implant length and diameter on primary stability in various bone densities is not well understood. Aim To in vitro study the effect of length and diameter on resonance frequency analysis (RFA), insertion torque (IT) and displacement (DP) measurements of dental implants in different implant site densities. Materials and methods Dental implants of four different diameters (Ø 3.5, 4.0, 4.5 and 5.0 mm) and three different lengths (7, 11 and 15 mm) (Neoss Ltd, Harrogate, UK) were placed in polyurethane blocks of three different densities (Sawbones Europe AB, Malmö, Sweden). The primary stability was assessed by RFA (ISQ) (Osstell, Osstell AB, Gothenburg, Sweden) and insertion torque measurements (ITmax in N cm) (iChiropo™, Bien‐Air Dental SA, Bienne, Switzerland). In addition, the blocks were mounted in a rig and a lateral force of 25 N cm was applied to the implants and the DP was measured in μm with a micrometer gauge placed on the opposite side of the load transducer. Statistical analyses using linear and quadratic models were applied. Results Implant length, diameter and block density were found to be significant independent predictors of RFA, ITmax, and DP measurements. Implant length had a strong effect, while the effect of diameter in general was subtle, particularly in the softest block. Conclusions Implant length affects primary stability more than implant diameter in polyurethane blocks of uniform density along the whole length of the tested 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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".