Bibliographic record
Abstract
BACKGROUND: The aims of this study were to identify that the differences in the natural history of patients with symptomatic and asymptomatic carotid stenosis may be reflected in differences in the expression of procoagulant protein factors. METHODS: Carotid artery plaques were obtained from 33 symptomatic and 4 asymptomatic patients with internal carotid artery stenosis of greater than 70%. These plaques were stained with monoclonal antibody against human tissue factor. Areas of staining for the cap and core were analysed using the analySIS computer programme. RESULTS: There were 37 patients, of whom 27 were male with a mean age 69.3 years and a range of 53 to 83 years. Statistical analysis using non-parametric tests revealed a significant increase in the area of positive staining for tissue factor in plaques taken from symptomatic patients when compared to those who were asymptomatic (P = 0001). Within the symptomatic patients group there was significantly increased tissue factor in the plaque core of those who were the most recently symptomatic (P = 0.003). CONCLUSIONS: The unstable carotid artery plaque is associated with significantly increased tissue factor expression in the cap and core. Plaques from the most recently symptomatic patients have significantly more tissue factor in the core and this may represent part of the mechanism responsible for plaque destabilisation. More research is needed in this important area. KEYWORDS: Tissue Factor; Carotid stenosis; Stroke; Plaque stability.
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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 | 0.001 |
| 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) | 0.001 | 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".