Bibliographic record
Abstract
PURPOSE OF REVIEW: The identification of new mutations continues to further our understanding of the molecular pathogenesis of essential thrombocythemia and related disorders, and offers opportunities for improvements in diagnosis, risk stratification and disease classification. RECENT FINDINGS: Molecular lesions in essential thrombocythemia affect two distinct pathways: cytokine signaling and transcriptional regulation. Signaling pathway mutations show a high degree of phenotypic specificity, in contrast to alterations in transcriptional pathways in which the same mutations are seen in diverse myeloid malignancies. Signaling pathway mutations are directly implicated in driving the myeloproliferation which characterizes essential thrombocythemia, whereas the phenotypic consequences of transcriptional pathway mutations are yet to be elucidated. The expanding lexicon of genetic abnormalities has revealed a surprising degree of clonal heterogeneity in essential thrombocythemia, although the clinical significance of this clonal complexity is currently unclear. Potential clinical applications for mutation screening include streamlining of the diagnostic process, improved risk stratification, and molecular distinction of essential thrombocythemia from related disorders such as polycythemia vera and myelofibrosis. SUMMARY: The genetic lexicon of essential thrombocythemia remains incomplete. Given the current acceleration in sequencing technology, further insights into essential thrombocythemia pathogenesis are likely close at hand.
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 | 0.001 | 0.001 |
| 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) | 0.002 | 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".