A 7-year-old boy with a nonfebrile seizure following a fall
Bibliographic record
Abstract
A previously healthy 7-year-old boy, who immigrated to Canada from Nicaragua 4 years prior, presented to his local hospital following a generalized tonic-clonic seizure with loss of consciousness at school. Minutes prior to seizure onset, he had hit his head after falling off a jungle gym. He then walked into the school building, where he experienced the seizure. In the Emergency Department, he was intubated for a Glasgow Coma Scale of three. A head computed tomography scan did not confirm the initially suspected intracranial bleed, but reported a left-sided posterior fossa mass. Phenytoin was initiated for seizure protection and the child was transferred to our Paediatric Critical Care Unit. Initial laboratory studies, including a complete blood count and differential, electrolytes, c-reactive protein, liver transaminases and renal and liver function parameters were noncontributory. An electroencephalogram showed excess delta activity, accentuated over the left posterior region, but no epileptiform activity. Further exploration of the medical history revealed that the patient had been experiencing nausea, vomiting, increasing blurry vision and mild headaches for 3 weeks. A 1-month family trip to Nicaragua 3 months prior to presentation was also noted. Subsequent magnetic resonance imaging (MRI) of the head suggested the diagnosis (Figure 1).
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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 | 0.001 | 0.010 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.014 | 0.010 |
| Insufficient payload (model declined to judge) | 0.003 | 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".