Anatomic Pattern of Intracerebral Hemorrhage Expansion
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: We sought to identify baseline determinants of the anatomic pattern of hematoma expansion in patients with intracerebral hemorrhage and spot sign. METHODS: We coregistered baseline and follow-up CT scans from 15 intracerebral hemorrhage patients and measured growth at each surface node from baseline to follow-up hematoma. We analyzed the effects of proximity to the spot sign or hematoma center on distance of expansion, controlling for covariates. RESULTS: There was substantial node-to-node variation in the extent of expansion around each hematoma surface (mean coefficient of variation for expansion distance, 0.43; 95% confidence interval, 0.39-0.48), indicating nonuniform expansion. Closer proximity to the hematoma center was independently associated with increased expansion (0.185 mm greater expansion for each 1 mm closer to the center; P<0.0001). Closer proximity to the spot sign was not independently associated with increased expansion in models including both terms. CONCLUSIONS: Hemorrhages expand nonuniformly around their surface with a tendency for greater expansion closer to their center. These findings provide a novel framework for analyzing mechanisms underlying hemorrhage growth and response to treatment.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".