Bibliographic record
Abstract
1. Genevieve Mercille, MD* 2. Luis H. Ospina, MD† 1. *Resident in Ophthalmology, Pediatric and Neuro-Ophthalmology Sections, Ste-Justine Hospital, Montreal, Quebec, Canada 2. †Associate Professor in Ophthalmology, University of Montreal, Montreal, Quebec, Canada After completing this article, readers should be able to: 1. List the diagnostic criteria for idiopathic intracranial hypertension (IIH). 2. Discuss the epidemiology, risk factors, and clinical manifestations of IIH in a pediatric population. 3. Describe the differential diagnoses and conditions associated with IIH. 4. Suggest appropriate therapeutic options for IIH. 5. Identify the principal complication of IIH and how it may be prevented. Idiopathic intracranial hypertension (IIH), previously referred to as pseudotumor cerebri or benign intracranial hypertension, was recognized initially in adults by Quincke in 1893 as “meningitis serosa.” (1) The syndrome is characterized by elevated intracranial pressure (ICP) without any evident underlying neurologic disease. The modified Dandy criteria, which were developed based on an adult population, can assist in establishing the diagnosis of IIH (Table 1) (2). | | || * Adapted from Friedman and Jacobson (3). Table 1. Diagnostic Criteria for Idiopathic Intracranial Hypertension Interestingly, children who have IIH may display a greater spectrum of clinical presentations than adults, and the disorder may have special epidemiologic characteristics in children. IIH occurs most commonly in young adults and rarely is seen in those older than age 45 years. The overall annual incidence is 0.9 per 100,000 individuals, (4) and there is a strong female predilection among affected adults. The incidence of IIH increases to 3.5 per 100,000 in women ages 20 to …
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.004 |
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".