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Record W4411634190 · doi:10.1007/s11912-025-01699-7

Hereditary Hematopoietic Malignancies: Considerations for Optimizing Diagnosis and Management

2025· review· en· W4411634190 on OpenAlex
Amy M. Trottier, Lea Cunningham, Lucy A. Godley

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueCurrent Oncology Reports · 2025
Typereview
Languageen
FieldMedicine
TopicAcute Myeloid Leukemia Research
Canadian institutionsDalhousie University
FundersNational Cancer InstituteNational Institutes of HealthQEII FoundationHealth Sciences Centre Foundation
KeywordsMedicineIntensive care medicineOncology

Abstract

fetched live from OpenAlex

PURPOSE OF REVIEW: Hereditary hematopoietic malignancies (HHMs) were once considered extremely rare. As diagnostic testing indications and methods have evolved, deleterious germline variants associated with increased risk of developing hematopoietic malignances are recognized increasingly. The purpose of this review is to summarize recent advances in knowledge, diagnostic, and treatment approaches for several well-known HHM predisposition disorders. RECENT FINDINGS: Patients often lack classic signs and symptoms typically associated with HHMs, may present at any age, and may not have a suggestive family history. Early identification of causative variants allows for timely anticipatory guidance for patients and family members and has important implications for optimizing treatment decisions. HHMs are not rare. With expanded genetic testing along with appropriate germline tissue selection and ancillary testing, predisposition variants can be identified early and inform appropriate surveillance and treatment decisions for patients and their families.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.741
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.142
GPT teacher head0.445
Teacher spread0.304 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it