Bibliographic record
Abstract
Cardiac embolism accounts for an increasing proportion of ischemic strokes and might multiply several-fold during the next decades. However, research points to several potential strategies to stem this expected rise in cardioembolic stroke. First, although one-third of strokes are of unclear cause, it is increasingly accepted that many of these cryptogenic strokes arise from a distant embolism rather than in situ cerebrovascular disease, leading to the recent formulation of embolic stroke of undetermined source as a distinct target for investigation. Second, recent clinical trials have indicated that embolic stroke of undetermined source may often stem from subclinical atrial fibrillation, which can be diagnosed with prolonged heart rhythm monitoring. Third, emerging evidence indicates that a thrombogenic atrial substrate can lead to atrial thromboembolism even in the absence of atrial fibrillation. Such an atrial cardiomyopathy may explain many cases of embolic stroke of undetermined source, and oral anticoagulant drugs may prove to reduce stroke risk from atrial cardiomyopathy given its parallels to atrial fibrillation. Non-vitamin K antagonist oral anticoagulant drugs have recently expanded therapeutic options for preventing cardioembolic stroke and are currently being tested for stroke prevention in patients with embolic stroke of undetermined source, including specifically those with atrial cardiomyopathy. Fourth, increasing appreciation of thrombogenic atrial substrate and the common coexistence of cardiac and extracardiac stroke risk factors suggest benefits from global vascular risk factor management in addition to anticoagulation. Finally, improved imaging of ventricular thrombus plus the availability of non-vitamin K antagonist oral anticoagulant drugs may lead to better prevention of stroke from acute myocardial infarction and heart failure.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.032 | 0.012 |
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".