Effects of clinical local factors on thickness and morphology of Schneiderian membrane: A retrospective clinical study
Bibliographic record
Abstract
BACKGROUND: It was informed that the thickness of maxillary sinus membrane may be affected by the local and patient-related factors in the literature. PURPOSE: The aim of this retrospective study is to evaluate factors that may have an influence of the thickness and morphology of the maxillary sinus membrane. MATERIALS AND METHODS: A total of 414 cone beam computed tomography images of 207 patients were evaluated. Radiographic parameters were evaluated at each maxillary premolar and molar tooth regions. Statistical analysis was performed to assess the association between the maxillary sinus mucosa thickness and morphology. The following factors including gender, periodontal bone loss (PBL), bone density, amount of residual alveolar bone at the edentulous space, vitality of the teeth present, and anatomical relationship between the sinus floor and posterior teeth were evaluated. RESULTS: The mean thickness of maxillary sinus membrane ranged between 1.47 to 2.92 mm and was significantly thicker in male subjects (P < .05). Positive correlation was detected between the sinus membrane thickness values in each posterior tooth region (P < .05). Thickening of the membrane was noted in 53% of the scans. The most commonly observed morphological change was flat thickening of the membrane (21%). No correlation was found between the evaluated local factors on the thickness and morphology of the maxillary sinus membrane (P > .05). CONCLUSIONS: Tooth vitality, residual alveolar bone height, and PBL seem to have no effect on the thickness and morphology of the maxillary sinus membrane.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".