A Three-rooted Deciduous Second Molar in a 13-year-old Caucasian Female
Bibliographic record
Abstract
Introduction: Several reports have been published highlighting accessory root formation in permanent molars. These studies have shown higher incidence of occurrence of accessory roots in patients of Mongolian, Taiwanese, Korean, Inuit, Native American and Indian descent. Very few reports have been published with a focus on accessory root formation in the primary dentition, in particular in the Caucasian population. Objective: This study was aimed at drawing attention to a rare morphological development in the Caucasian population. Case Presentation: This report presents a case of a 13-year-old Caucasian female with a three-rooted mandibular second molar tooth #T. The tooth was surgically removed, with some degree of difficulty, and upon inspection of the tooth following removal, it was observed that an accessory root was present. Conclusions: The presence of an accessory root may be demonstrated radiographically, but often is only discovered after excavation of the pulp chamber or following removal of the tooth itself. As such, it is important for the astute clinician to consider the potential for the presence of an accessory root, and to appreciate the potential complications an accessory may cause during endodontic or surgical treatment. Appropriate imaging should be obtained preoperatively if an accessory root is suspected, and treatment planning should be adjusted accordingly, in order to optimize successful treatment.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".