Clinical application of susceptibility-weighted imaging in the evaluation of leptomeningeal collateralization
Bibliographic record
Abstract
The feasibility of using susceptibility-weighted imaging (SWI) in a clinical setting was assessed for quantifying leptomeningeal collateralization.Eighteen patients with stroke and acute infarction underwent diffusion-weighted imaging, SWI, perfusion-weighted imaging, and magnetic resonance angiography within 3 days after symptom onset. Lesions were evaluated by the Alberta Stroke Program Early CT score (ASPECTS), based on mean transit time, SWI, and cerebral blood volume (CBV).For evaluating ischemic penumbra and leptomeningeal collateralization, the SWI-ASPECTS significantly correlated, respectively, with mean transit time and CBV-ASPECTS (Spearman test, r = 0.793 and 0.682; P < .001, both).The SWI may be useful to quantify leptomeningeal collateralization in patients with acute cerebral infarction.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".