CLINICAL AND RADIOLOGICAL CHARACTERISTICS OF THE DENTAL AND JAW SYSTEM STATE IN PERSONS WITH LOW MINERAL DENSITY BONE TISSUE
Bibliographic record
Abstract
Introduction. Despite the fact that the process of osseointegration has been studied for many years, a number of issues concerning the specifics of dental implantation in the case of osteopathies of various genesis, ensuring good primary stability of the implant, further forecasting of dental implantation and prevention of postoperative complications remain unresolved. The purpose. To study the state of bone tissue in people with defects of dentition against the background of osteopathy Materials and methods. 148 patients with dentition defects of young and middle age were examined. All patients underwent densitometric studies of bone tissue to determine its mineral density. For the qualitative characterization of the cortical layer of the lower jaw, the mandibular-cortical index according to Klemetti E. and co-authors was used. The optical density of the bone tissue of the jaws was measured using Image Q software, developed in 2007 by the National Institutes of Health (Canada), which allows the analysis of any selected area of the jawbone in conventional brightness units (units of brightness) in gradations of gray: from 0 to 256. Results. According to the mandibular-cortical index, a domination of C2 bone tissue type was found in men vs. women (55.41 vs. 32.43%). At the same time, in women with osteopenia, the C3 bone tissue type was diagnosed in 60.81% compared to 33.78% of men with osteopenia. However, the results of the study established that in men aged 18–44, the average values of the optical density of bone tissue probably did not differ from those in the comparison group (p>0.05) and at the same time, they were significantly lower: by 18.35% – in men of the older age group (р<0.05) and by 29.12% – among women of the older age group (р<0.001). Still, the optical density of bone tissue was characterized by lower values in women vs. men with osteopenia, and it tended to decrease with increasing age of the subjects, regardless of gender. Conclusions. The conducted studies made it possible to conclude that the optical density of the bone tissue of the jaws in patients with osteopenia decreased with increasing age of the patients, but women had the lowest values in both age groups.
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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 | 0.001 | 0.001 |
| 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) | 0.002 | 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".