Correlation between the Bone Density Recorded by a Computerized Implant Motor and by a Histomorphometric Analysis: A Preliminary In Vitro Study on Bovine Ribs
Bibliographic record
Abstract
PURPOSE: The purpose of the present preliminary in vitro study on bovine ribs was to validate a new intraoperative site-specific classification of bone Density Index (IDI), obtained by an innovative computerized implant motor, by correlating these data with the data obtained by the histomorphometrical evaluation of the same samples. MATERIALS AND METHODS: Five segments of bovine ribs were used, and a total of 22 perforations were performed. A computerized implant motor ("Torque Measuring Motor") was used to evaluate the bone density, which was classified into four classes: ID1, ID2, ID3, and ID4. Histomorphometrical analysis of bone density, expressed as percentage of bony trabeculae over the total biopsy area, was also performed. The data of bone density obtained by the implant motor were statistically correlated with the histomorphometrical results. RESULTS: A significant positive correlation was found between the bone density measured by the implant motor and the bone density assessed by histomorphometry (r = 0.89, p < .0001). Moreover, a significant positive correlation in D1, D2, and D4, whereas a negative, not significant correlation in D3 was found. CONCLUSION: Within the limitations of this in vitro study, the intraoperative site-specific classification of bone density, obtained with this innovative system, could be helpful for the clinician to tailor the surgical protocol to the different situations in implant dentistry.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".