Abutment Rotational Freedom Evaluation of External Hexagon Single‐Implant Restorations after Mechanical Cycling
Bibliographic record
Abstract
PURPOSE: The purpose of this study was to evaluate the rotational freedom between implant and abutment counterpart of two abutments types over external hexagon implants submitted to mechanical cycling. MATERIALS AND METHODS: Ten implants with external hexagon (3.75 mm × 13 mm), five cast abutments, and five premachined abutments both with 4.1 mm plataform size were used in this study. Ten metallic crowns were fabricated using the two types of abutments and were fixed to each implant using titanium screws (Ti6Al4V). Rotational freedom measurements were made before and after the cast procedure and after the mechanical cycling. Groups were classified according to the rotational misfit register using University of California, Los Angeles abutment and implants as new (group 1 = G1); using crowns and implants after crown casting (group 2 = G2); and using crowns and implants after mechanical cycling (group 3 = G3). Oblique loading of 120N at 1.8 Hz and 5 × 10(5) cycles was applied on specimen. RESULTS: Statistical analysis (p < .05) showed that no significant difference was observed when cast abutment was compared with premachined abutment after casting (p = .390) and mechanical cycling (p = .439); however, significant difference was noted before the casting (p = .005) with higher values for the cast abutments. CONCLUSIONS: Within the limitations of this in vitro study, it could be concluded that the abutment type used do not influenced the rotational freedom after casting and the amount of applied cycles (500,000 cycles) was not sufficient to significantly alter the values of rotational freedom at the implant/abutment joint.
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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 | 0.000 | 0.001 |
| 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".