Sinus Width Analysis and New Classification with Clinical Implications for Augmentation
Bibliographic record
Abstract
PURPOSE: To measure the distances between the medial and lateral sinus wall (sinus width [SW]) at different levels on cone beam computed tomography (CBCT) and apply those SW values to formulate a new sinus classification. MATERIALS AND METHODS: Edentulous sites adjacent to maxillary sinuses with inadequate residual bone height (RBH) were included from the CBCT database. SW was measured at the heights of 1, 3, 5, 7, and 9 mm from the sinus floor. Mean SW was stratified into different groups by RBH, study sites (first and second premolars and molars), and measurement levels. Statistical analyses were conducted with commercially available software (IBM SPSS Statistics 19, SPSS Inc., Chicago, IL, USA). RESULTS: A total 186 patients (mean age 50.4 years) with 267 edentulous sites were included. Mean SW was wider at molar sites, higher measurement levels, and sites with less RBH. Narrow, average, or wide sinuses were classified based on the 33rd and 67th percentile SW values at 1-, 5-, and 9-mm measurement levels, respectively. CONCLUSIONS: SW at different levels relating to sinus floor elevation was measured. The proposed classification could contribute to estimate the difficulty of sinus augmentation, useful for the selection of surgical approaches. Further studies are required to testify its clinical implications.
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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".