International consensus on histologic diagnosis of early hepatocellular neoplasia
Bibliographic record
Abstract
1. The precursor lesions for the development of hepatocellular carcinoma are believed to be high-grade dysplastic nodules. These lesions have atypical and proliferative features that distinguish them from normal or cirrhotic liver but are not sufficient for the diagnosis of carcinoma. 2. Individual HGDN are often heterogeneous and complete sampling may reveal regions of carcinoma within these otherwise benign lesions. 3. Invasion of stroma is considered a definitive feature of HCC. However, this feature is not always present in early HCC and is seldom found in needle biopsies. 4. Accurate diagnosis of dysplastic nodules and well-differentiated HCC requires skill and experience. However, accurate diagnosis with needle biopsies may be impossible if the highest grade of atypia is not sampled. Fine needle aspiration is not appropriate for small lesions that are expected to be early hepatic neoplasia. This technique should be reserved for suspected moderate- or poorly differentiated HCC.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 teacher head, 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".