Cascaded techniques for improving emphysema classification in computed tomography images
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Bibliographic record
Abstract
The previous studies demonstrated the effectiveness of the multi-fractal based method for the classification of histo-pathologicalcases by calculating the local singularity coefficients of an image using different intensity measures. This paper proposed toimprove the previous results by investigating the features derived from the combination of the alpha-histograms and the multifractaldescriptors in the classification of Emphysema in computed tomography (CT) images. The performances of the classifiersare measured by using the classification accuracy (error matrix) and the area under the receiver operating characteristic curve(AUC). And further, the experimental results compared well with the local binary patterns (LBP) approach, a state-of-the-artmeasure for pulmonary Emphysema. The results also show that the proposed cascaded approach significantly improves theoverall classification accuracy.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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 it