Bibliographic record
Abstract
Introduction & Objective: Air-filled canals that is originated from the mastoid process trunk of the temporal bone and the middle ear have been introduced as mastoid air cells.One of the most important aspects of investigation of mastoid air cells pneumatization is that it can be considered as a prognosis for the infection of the middle ear.Cone beam Computed Tomography (CBCT) is a new technique recently known as dental CT imaging, which is used in dentistry.Regarding the fact that in previous studies, the vast age range has been studied and most of them were based on gender and only CT technique was used for the purpose of evaluation of mastoid air cells pneumatization, therefore, the present study was conducted to investigate the mastoid air cells pneumatization using the CBCT technique and compare it in different age groups and genders.Materials and Methods: In this descriptive-analytical study, a stereotypes of CBCT of 200 patients (100 males, 100 females) who referred to Oral and Maxillofacial Radiology Department of Tabriz Dental School were used and samples were examined in coronal, axial, and sagittal sections.Data were analyzed by descriptive statistics (percentage) and Chi-square test by SPSS 16 software.The value of p-value in this study was considered as 0.05.Results: The Chi-Square test showed a significant difference in the frequency of pneumatization based on gender (p<0.05).Chi-square test showed a significant difference in the frequency of pneumatizationdegree based on age groups (p<0.05).Chi-square test did not show a significant difference in the frequency of pneumatization based on the side of mastoid bone (p>0.05).Conclusion: The results of present study showed that the degree of pneumatization of mastoid air cells has a significant difference based on gender and age groups and CBCT technique is a suitable method for studying mastoid air cells pneumatization.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.940 | 0.902 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".