Gene expression profiling of hepatocellular cancer identifies a consistent pattern in cancerous and distant liver tissue: Arguments for a field defect
Bibliographic record
Abstract
6099 The genetic changes that accompany hepatocellular cancer (HCC) are notoriously variable, though the cancer itself may develop in the context of an organ-wide field defect. We hypothesized that the pattern of gene expression reflecting such a field defect would persist in the HCC itself, and would be distinct from patterns of liver gene expression in chronic liver disease patients who have not developed HCC. Using a 19K human microarray, we determined gene expression levels in 15 HCC samples and 15 liver samples taken at least 5 cm away from the original HCC (distant liver tissue, DLT). These were compared to liver biopsies from patients with chronic liver disease but no HCC (86 HCV biopsies, 18 HBV biopsies). All gene expression changes were normalized to the baseline level of gene expression in 20 normal liver biopsies. Insisting on a high statistical filter (p
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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 | 0.000 | 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) | 0.001 | 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".