Bibliographic record
Abstract
Background: Etiologic overlaps may occur in patients with ischemic stroke depending on the diagnostic investigations and classification criteria. Methods: Consecutive ischemic stroke patients admitted in Mackenzie hospital, Canada from August 2003 to August 2004 underwent a standard battery of diagnostic investigations by stroke neurologists. Stroke mechanism was defined based on the Toast criteria. Stroke topography subtypes were small and large artery territory infarcts. Results: A total of 302 stroke patients (159 female, 143 male) were registered. Small and large artery territory infarcts consisted 25.5% and 74.5% of our topography respectively. Etiologic overlaps were found in 17.5% of the patients. Cardiac source of embolism was significantly more frequent in patients with large artery territory infarcts (p= 0.002) but frequency difference of corresponing large artery atherosclerotic stenosis was not significant in these topographies (p= 0.378). Etiologic overlaps were more frequent in patients with small artery territory infarcts (p= 0.004). Conclusion: Etiologic overlaps are frequent and should be considered for optimal management of the ischemic stroke patients. Key words: Etiology, Mechanism, Overlap, Stroke, Coexistence
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".