Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it