Transmission Electron Microscopy: A Surgical Pathology Tool for Neuroblastoma
Bibliographic record
Abstract
Pediatric small round blue cell tumors (PSRBCT) are an intriguing and challenging collection of neoplasms. Light microscopy of small round blue cell tumors identifies small round cells. They harbor a generally hyperchromatic nucleus and relatively scanty basophilic cytoplasm. Pediatric small round blue cell tumors include several entities. Usually, they incorporate Wilms tumor, neuroblastoma, rhabdomyosarcoma, Ewing sarcoma, retinoblastoma, lymphoma, and small cell osteosarcoma, among others. Even using immunohistochemistry, the differential diagnosis of these neoplasms may be controversial at light microscopy. A faint staining or an ambiguous background can deter pathologists from making the proper diagnostic decision. In addition, molecular biology may provide an overwhelming amount of data challenging to distinguish them, and some translocations may be seen in more than one category. Thus, transmission electron microscopy (TEM) can be extremely valuable. Here we emphasize the modern protocol for TEM data of the neuroblastoma. Tumor cells with tangles of cytoplasmic processes containing neurosecretory granules can diagnose neuroblastoma.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.008 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 0.006 |
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".