Keratocystic odontogenic tumour: reclassification of the odontogenic keratocyst from cyst to tumour.
Bibliographic record
Abstract
range and lesions in this range resulted in the greatest number and proportion of recurrences. The recurrence rate of 29% in our case series was consistent with previously established data; all recurrences occurred within 2 years post-intervention. The incidence of primary lesions was highest in the age group 70-79 years; most lesions occurred in the posterior mandible. WHO"s reclassification of the OKC as the KCOT based on behaviour, histology and genetics underscores the aggressive nature of the lesion and should motivate clinicians to manage the disease in a correspondingly aggressive manner. The most effective interventions for the KCOT are either enucleation with Carnoy"s solution, or marsupialization with later cystectomy. Future treatment may involve molecular-based modalities, which may reduce or eliminate the need for aggressive surgical management.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".