Gene-Set Reduction for Analysis of Major and Minor Gleason Scores Based on Differential Gene-Set Expressions and Biological Pathways in Prostate Cancer
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The Gleason score (GS) plays an important role in prostate cancer detection and treatment. It is calculated based on a sum between its major and minor components, each ranging from 1 to 5, assigned after examination of sample cells taken from each side of the prostate gland during biopsy. A total GS of at least 7 is associated with more aggressive prostate cancer. However, it is still unclear how prostate cancer outcomes differ for various distributions of GS between its major and minor components. This article applies Significance Analysis of Microarray for Gene-Set Reduction to a real microarray study of patients with prostate cancer and identifies 13 core genes differentially expressed between patients with a major GS of 3 and a minor GS of 4, or (3,4), vs patients with a combination of (4,3), starting from a less aggressive GS combination of (3,3), and moving toward a more aggressive one of (4,4) via gray areas of (3,4) and (4,3). The resulting core genes may improve understanding of prostate cancer in patients with a total GS of 7, the most common grade and most challenging with respect to prognosis.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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