Bibliographic record
Abstract
Hepatocellular carcinoma (HCC) has progressed within the last 10–15 years from being a cancer that was almost universally fatal to one that is potentially curable in the majority of cases. However, for this to happen it is essential that the HCC is found early. Patients at risk for HCC have to undergo regular surveillance with ultrasound. Lesions detected during surveillance have to be aggressively investigated and aggressively treated. If HCC can be diagnosed when the lesion is 90%.1 2 Treated patients remain at risk for the development of a second primary, but the treated HCC can be completely cured. Ultrasound surveillance identifies many small lesions in the liver that may or may not be HCC. These include dysplastic nodules, cirrhotic nodules and haemangioma. Making the distinction between HCC and haemangioma is usually not difficult, but distinguishing between cirrhotic nodules, dysplastic nodules and HCC can be difficult. The tools available include contrast-enhanced radiological imaging, or biopsy. It is possible to diagnose HCC without biopsy. Indeed, if the typical radiological features are present, the diagnostic accuracy is almost 100%. The highly characteristic features are that in the arterial phase of a dynamic contrast-enhanced study the HCC shows hypervascularity—that is, it gives a brighter signal that the surrounding liver. In the portal venous phase of the study and in the delayed phase ∼3 min …
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How this classification was reachedexpand
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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.002 | 0.003 |
| 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; both teacher heads agree on what is shown here.
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".