Genomic Taxonomy of Aggressive B-Cell Lymphoid Neoplasms
Bibliographic record
Abstract
Aggressive B-cell lymphomas are a heterogeneous group of neoplasms, organized in the current classifications into more than 20 categories on the basis of morphology, immunophenotype, clinical presentation, and limited molecular features. Over the past 25 years, there has been an exponential accumulation of detailed genomic characterizations of these lymphomas. Many defined categories have been confirmed as relatively homogeneous, fulfilling the classification ideal of sharing core biological hallmarks. However, the largest group, diffuse large B-cell lymphoma, not otherwise specified, which makes up 70-74% of the patients, has been revealed to be remarkably heterogeneous at a genomic and biological level. In this review, we summarize the current state of knowledge and then propose an evolution of the classification of aggressive B-cell lymphomas to a genomics-informed taxonomy built around normal B-cell development and the different modes by which lymphomas achieve key hallmarks of cancer-hallmarks that can inform on patient management.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".