Bibliographic record
Abstract
OBJECTIVE: Mastoiditis, subperiosteal abscess and sigmoid vein thrombosis are the most common suppurative complications of acute otitis media (AOM). Luc's abscess, a subperiosteal temporal collection, is an infrequent complication with a particularly benign course. PATIENTS: Two children, aged 5 years, presented with AOM complicated by an atypical abscess deep to the temporalis muscle, with no evidence for mastoid or zygomatic arch involvement. INTERVENTION(S): Computed tomographic scan was performed in only 1 child. In both children, treatment included antibiotic therapy, grommet insertion, and local surgical drainage of the temporalis abscess. In addition, a cortical mastoidectomy was performed in the patient who did not undergo computed tomography, based on clinical assessment. MAIN OUTCOME MEASURE(S): Clinical improvement, resolution of symptoms. RESULTS: Both patients recovered shortly following the surgical drainage. Mastoidectomy was poor in findings and was concluded as redundant. CONCLUSION: Luc's abscess is associated with relatively little morbidity and requires a more limited surgical intervention. Computed tomographic scan is of great value to evaluate the extent of the disease and prevent needless mastoidectomy.
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.
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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".