Bibliographic record
Abstract
A nine-year-old girl presented with a four-day history of a growing mass under the right side of her tongue. The mass had been steadily increasing in size, but was not affecting her ability to swallow, speak, chew or breathe. The lesion was not tender or painful. It was light blue in colour. The patient had previously been well and had not experienced any recent nausea, vomiting, fever or weight loss. She had no history of oral trauma. On examination, the patient appeared well. The mass was approximately 6 cm long and 3 cm wide, fluid-filled, fluctuant, bluish-red in colour and nontender to palpation. It was located beneath the right side of the tongue and extended to the base of the mouth (Figure 1). The patient's oral cavity and palate appeared otherwise normal. No cervical lymphadenopathy was present, and the patient's neck was supple. ... Ranulas and mucoceles are probably the most common disorders of the salivary glands. The development of a mucocele is dependent on the disruption of flow from the secretory apparatus of the salivary glands. The majority are extravasation mucoceles in which there is pooling of mucus in the connective tissue, presumably arising from trauma to a salivary duct. Less common are retention mucoceles, resulting from ductal obstruction and retention of saliva within the ductal system. The two types of mucoceles cannot be distinguished clinically. Ranulas are similar to mucoceles, but involve the major salivary glands. There are two types of ranulas: oral and cervical. Oral ranulas result from pooling of mucus superior to the mylohyoid muscle, while cervical ranulas are caused by mucus extravasation along the fascial planes of the neck.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.009 | 0.006 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".