Bibliographic record
Abstract
Brain metastases from soft tissue sarcomas (STS) occur late and relatively rarely, most commonly after lung metastases have developed. Furthermore, they are most commonly intraparenchymal in distribution. We describe two cases of histologically confirmed intracranial metastatic soft tissue leiomyosarcomas. In both cases all the nodular metastases measuring 10 mm in diameter or less could be easily detected in the leptomeningeal spaces by MRI. However, as the lesion enlarges it is difficult to recognize the site of origin, and the mass appears and behaves as intra-axial. Lesions located in the leptomeningeal spaces and in the perivascular space can be extremely small, which makes their detection problematic. For this reason we believe that in this context, MRI global gadolinium enhanced imaging using contiguous 1 mm slice thickness acquisition (TR 23 ms,TE 8 ms 512×512 matrix) is preferable, since the patient's management may vary depending on the multiplicity and location of the lesions.
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 | 0.001 | 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 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".