Inter-observer Variation of the Alberta Stoke Program Early CT Score (ASPECTS) among Radiologists in the Philippine General Hospital
Bibliographic record
Abstract
Objective. To determine the inter-observer variation of ASPECTS among radiologists in the Philippine General Hospital (PGH), particularly between trainee radiologists and an expert reader. Methods. Thirty (30) cranial CT scan studies of clinically-diagnosed, non-hemorrhagic stroke patients were analyzed by 9 trainee radiologists (3 fellows, and 3 senior and 3 junior residents) and one expert reader. Data analysis involved determining the levels of agreement within and across groups, and against the expert reader. Results and Conclusion. There was moderate agreement (kappa = 0.60) between the junior residents and the expert reader, and substantial agreement between the senior residents and the expert reader (kappa = 0.70), as well as between the fellows and the expert reader (kappa = 0.63). Over-all, there was substantial agreement between the trainee radiologists and the expert reader (kappa = 0.63). It can be concluded that the interpretation of trainee radiologists in PGH, particularly that of a senior resident or a fellow, is comparable with that of an expert reader, and can, thus, be useful in cases where an interpretation of a CT scan procedure in a clinically-diagnosed stroke patient is needed.
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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 | 0.009 | 0.032 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".