Het reuzenhemangioom in de lever: diagnostiek en behandeling
Bibliographic record
Abstract
A liver haemangioma is a benign, usually small tumour comprised of blood vessels, which is often discovered coincidentally; giant haemangiomas are defined as haemangiomas larger than 5 cm. The differential diagnosis includes other hypervascular tumours, such as hepatocellular adenoma, hepatocellular carcinoma, metastasis of a neuro-endocrine tumour or renal cell carcinoma.- The diagnosis is based on abdominal ultrasonography and can be confirmed by a CT or MR scan. A wait-and-see approach is justified in patients without symptoms or with minimal symptoms, even in the presence of a giant haemangioma. Surgical resection of a giant haemangioma is only necessary when the preoperative diagnosis is inconclusive, or when the haemangioma leads to mechanical symptoms or complications. Extirpation is the only effective form of treatment of the giant haemangioma; enucleation is preferred over partial liver resection. A known complication of a giant haemangioma is the occurrence of disseminated intravascular coagulation, the Kasabach-Merritt syndrome; intervention is then demanded
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 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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.021 | 0.007 |
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".