Bibliographic record
Abstract
Abstract Learning Objectives After completing this course, the reader will be able to: List the key clinical features of PMBCL.Discuss the literature on chemotherapy in PMBCL and the role of radiotherapy in PMBCL.Describe the pathologic features of PMBCL. Access and take the CME test online and receive 1 AMA PRA category 1 credit at CME.TheOncologist.com Primary mediastinal large B-cell lymphoma represents a distinct entity with unique clinicopathologic features and a molecular gene-expression signature reminiscent of nodular sclerosis subtype of classical Hodgkin's lymphoma. Recent studies, including those using a refined molecular signature, suggest that the outcome is more favorable than that of diffuse large B-cell lymphoma. Using historical comparisons, dose-dense and dose-intensive regimens may be more effective than cyclophosphamide, doxorubicin, vincristine, and prednisone chemotherapy; however, the impact of adding rituximab to these regimens and effect on outcome comparisons is unknown. Clinical trials exploring these questions in addition to the benefit of consolidative radiotherapy are necessary to definitively answer these questions.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".