Bibliographic record
Abstract
Primary mediastinal large B-cell lymphoma (PMBCL) is a separate entity in the World Health Organization's classification, based on clinicopathologic features and a distinct molecular signature that overlaps with nodular sclerosis classic Hodgkin lymphoma (cHL). Molecular classifiers can distinguish PMBCL from diffuse large B-cell lymphoma (DLBCL) using ribonucleic acid derived from paraffin-embedded tissue and are integral to future studies. However, given that ∼5% of DLBCL can have a molecular PMBCL phenotype in the absence of mediastinal involvement, clinical information remains critical for diagnosis. Studies during the past 10 to 20 years have elucidated the biologic hallmarks of PMBCL that are reminiscent of cHL, including the importance of the JAK-STAT and NF-κB signaling pathways, as well as an immune evasion phenotype through multiple converging genetic aberrations. The outcome of PMBCL has improved in the modern rituximab era; however, whether there is a single standard treatment for all patients and when to integrate radiotherapy remains controversial. Regardless of the frontline therapy, refractory disease can occur in up to 10% of patients and correlates with poor outcome. With emerging data supporting the high efficacy of PD1 inhibitors in PMBCL, studies are underway that integrate them into the up-front setting.
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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 | 0.000 |
| 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) | 0.007 | 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".