Bibliographic record
Abstract
Approximately 25% to 30% of patients with diffuse large B-cell lymphoma (DLBCL) present with limited-stage disease, typically defined as those with nonbulky (<10 cm) Ann Arbor stage I or II disease, without B-symptoms and with sites that can be encompassed within a radiation field. A variety of treatment approaches have been used, which have largely relied on the administration of systemic therapy followed by involved-field radiation therapy (IFRT) to all sites of disease. The use of IFRT has been associated with improved local control, but a significant impact on long-term outcome has not been demonstrated. Although the inclusion of IFRT may allow for an abbreviated course of chemotherapy to be administered, this benefit must be weighed against the potential for radiation-induced acute and delayed toxicity. With the advent of improved systemic therapy, the routine use of IFRT in all patients with limited-stage DLBCL seems no longer justifiable. A tailored-therapy approach, with choice of treatment guided by patient performance status and chemotherapy tolerance, sites of disease involvement, clinical risk factors, and early treatment response would seem rational. Ultimately, greater biologic insight into the heterogeneity of DLBCL will likely result in a personalized treatment approach that relies more on biologic characteristics than stage of disease.
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 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".