Inter-rater reliability of modified Alberta Stroke program early computerized tomography score in patients with brain infarction.
Bibliographic record
Abstract
BACKGROUND: The Alberta Stroke Program Early Computerized Tomography Score (ASPECTS) was used to detect significant early ischemic changes on brain CT of acute stroke patients. We designed the modified ASPECTS and compared it to the above system based on the inter-rater reliability. METHODS: A cross-sectional validation study was conducted based on the inter-rater reliability. The CT images were chosen from the stroke data bank of Ghaem hospital, Mashhad in 2010. The inclusion criteria were the presence of middle cerebral artery territory infarction and performance of CT within 6 hours after stroke onset. Axial CT scans were performed on a third-generation CT scanner (Siemens, ARTX, Germany). Section thickness above posterior fossa was 10 mm (130 kV, 150 mAs). Films were made at window level of 35 HU. The brain CTs were scored by four independent radiologists based on the ASPECTS and modified ASPECTS. The readers were blind to clinical information except symptom side. Cochrane Q and Kappa tests served for statistical analysis. RESULTS: 24 CT scans were available and of sufficient quality. Difference in distribution of dichotomized ≤7 and >7 ASPECT scores between four raters was significant (Q=13.071, df=3, p=0.04). Distribution of dichotomized <6 and ≥6 scores based on modified ASPECT system between 4 raters was not significantly different (Q=6.349, df=3, p=0.096). CONCLUSIONS: Modified ASPECT method is more reliable than ASPECTS in detecting major early ischemic changes in stroke patients candidated to tPA thrombolysis.
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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 | 0.016 | 0.037 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".