Bibliographic record
Abstract
Arrhythmogenic right ventricular cardiomyopathy (ARVC) has evolved from postmortem pathology at to a diagnosable clinical condition, and holds promise for definitive genetic diagnosis. Its prevalence is between 1/1,000 and 1/5,000, with 10% of deaths occurring before age 19 and 50% before age 35. When analyzed against age-specific norms, the electrocardiography (ECG) and signal-averaged ECG (SAECG) have moderate sensitivity for ARVC. Endomyocardial biopsy in young individuals with ARVC demonstrates fibrosis more frequently than fatty infiltration, and is convincing for the diagnosis in approximately 1/3 (often in patients who would not otherwise be diagnosed), but has a recognized complication rate of 2%. Newer technologies of magnetic resonance imaging and voltage mapping hold promise but require further assessment in young individuals suspected to have ARVC. Genetic diagnosis of one of several desmosomal mutations is positive in an approximately 50% of suspected patients, and may provide clues to the pathophysiology of the disease. Serial studies of myocardial function, ambulatory electrocardiography, and SAECG parameters may be useful in risk stratification of identified patients, although their applicability to genetically identified asymptomatic individuals has not been studied.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".