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
Myocarditis is an inflammatory disease of the heart muscle with a wide range of potential etiological factors and consequently varying clinical patterns across the world. In this review, we address the epidemiology of myocarditis. Myocarditis was considered a rare disease until intensified research efforts in recent decades revealed its true epidemiological importance. While it remains a challenge to determine the true prevalence of myocarditis, studies are underway to obtain better approximations of the proportions of this disease. Nowadays, the prevalence of myocarditis has been reported from 10.2 to 105.6 per 100,000 worldwide, and its annual occurrence is estimated at about 1.8 million cases. This wide range of reported cases reflects the uncertainty surrounding the true prevalence and a potential underdiagnosis of this disease. Since myocarditis continues to be a significant public health issue, particularly in young adults in whom myocarditis is among the most common causes of sudden cardiac death, improved diagnostic and therapeutic procedures are necessary. This manuscript aims to summarize the current knowledge on the epidemiology of myocarditis, new diagnostic approaches and the current epidemiological impact of the COVID-19 pandemic.
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 | 0.008 | 0.047 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.012 | 0.006 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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