Healing of implants installed in over- or under-prepared sites--an experimental study in dogs
Bibliographic record
Abstract
OBJECTIVE To study bone healing at implants installed with different insertion torques. MATERIAL AND METHODS In six Labrador dogs, all mandibular premolars and first molars were extracted. After 4 months of healing, flaps were elevated, and two implant sites were prepared at each side of the mandible. In the right side of the mandible, the distal sites were prepared conventionally, while the mesial sites were over-prepared by 0.2 mm. As a consequence, a final insertion torque of ~30 Ncm at the distal and a minimal insertion torque close to 0 Ncm at the mesial sites were obtained. In the left sides of the mandible, however, the recipient sites were underprepared by 0.3 mm resulting in an insertion torque of ≥ 70 Ncm at both implants. Cover screws were applied, and flaps sutured to fully submerge the experimental sites. After 4 months, the animals were sacrificed and ground sections obtained for histological evaluation. RESULTS The mineralized bone-to-implant contact was in the range of 55.2-62.1%, displaying the highest value at implants with ~30 Ncm insertion torque and the lowest value at the implant sites with close to 0 Ncm insertion torque. No statistically significant differences were revealed. Bone density was in the range of 43.4-54.9%, yielding the highest value at implants with ≥ 70 Ncm insertion torque and the lowest at the implant sites with close to 0 Ncm insertion torque. The difference between the sites of ~30 Ncm and the corresponding ≥ 70 Ncm insertion torque reached statistical significance. CONCLUSIONS Similar amounts of osseointegration were obtained irrespective of the insertion torque applied. Moreover, implants installed in sites with close to 0 Ncm insertion torque may properly osseointegrate as well.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| 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 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".