An afebrile seizure in a previously healthy 9-year-old boy
Bibliographic record
Abstract
A 9-year-old, previously healthy male presented to a rural hospital with a first presentation of a seizure described as right eye deviation and tonic-clonic movements. The patient was administered a Keppra loading dose which aborted the seizure. Initial blood work was reportedly normal, except for an elevated creatinine of 100 μmol/L. A CT scan of his head revealed an ill-defined opacity, suspicious for a mass. Three days prior, he was diagnosed with a viral illness in the setting of a week-long history of sore throat, dyspnea, and lymphadenopathy (COVID-negative). Transport to a paediatric tertiary care centre was unremarkable, except for elevated blood pressure readings thought unreliable due to agitation. On arrival, he was noted to have fluctuating levels of consciousness and would complain intermittently of headaches. He was afebrile, with a heart rate of 80 beats per minute and a blood pressure of 150/110 mmHg. He had enlarged, erythematous tonsils with exudate. No signs of meningeal irritation and no focal neurological signs were observed. Upon arrival at our centre, an investigation was performed, which revealed the diagnosis.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 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".