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
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 …
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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.002 |
| Bibliometrics | 0.001 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it