Awareness-knowledge level and practice of two dentistry specialties dentists regarding juxta-apical radiolucency
Bibliographic record
Abstract
Introduction: Mandibular third molar extraction is one of the most common procedures in oral and maxillo facial surgery.The procedure may result in several complications, such as injury of inferior alveolar nerve (IAN) and postoperative paresthesia/dysesthesia. Objectives: To evaluate the awarenessknowledge level and practice of dentists who received specialization train ing in oral and maxillofacial radiology and oral and maxillofacial surgery regarding juxtaapical radiolucency (JAR).Material and methods: Dentist participants who received specialization training and volunteered to participate were divided into two groups according to their specialization: group 1 -oral and maxillofacial radiology; group 2oral and maxillofacial surgery.A special questionnaire was prepared for this study and participants provided answers facetoface.The form consisted of two parts: part 1 -personal information, and part 2 -awarenessknowledge level and practice regarding JAR.In part 2, dentists were asked questions on different panoramic radiography images containing JAR in a slide show.Pearson's c 2 test was applied for statistical analysis.Results: A total of 66 volunteers divided into two groups [group 1: n = 32 (43%); group 2: n = 34 (57%)] partici pated in the current study.The preliminary diagnosis of JAR was mostly associated with anatomical formation (group 1: 63.1%; group 2: 64.1%) and odontogenic/nonodontogenic lesions (group 1: 41.8%; group 2: 48.2%).Usually, participants thought that such a radiolucency would affect extraction method (group 1: 68.8%; group 2: 63.5%), posed a risk for IAN (group 1: 67.5%; group 2: 69.4%), and negatively affect healing process (group 1: 66.3%; group 2: 61.2%).A small ratio of participants was aware of JAR (group 1: 18.8%; group 2: 2.9%). Conclusions:The awarenessknowledge level of dentists who received training in oral and maxillofacial ra diology and oral and maxillofacial surgery regarding JAR was low.The practice of participants of both specialties towards JAR were variable.
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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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".