MétaCan
Menu
Back to cohort
Record W4293776726 · doi:10.3390/curroncol29090491

Management of Acute Myeloid Leukemia: A Review for General Practitioners in Oncology

2022· review· en· W4293776726 on OpenAlex

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.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueCurrent Oncology · 2022
Typereview
Languageen
FieldMedicine
TopicAcute Myeloid Leukemia Research
Canadian institutionsTerry Fox Research InstituteFraser HealthUniversity of British ColumbiaVancouver Coastal Health
Fundersnot available
KeywordsMedicineMyeloid leukemiaAzacitidineVenetoclaxOncologyInternal medicineIntensive care medicineRisk stratificationMalignancyLeukemiaChronic lymphocytic leukemia

Abstract

fetched live from OpenAlex

Acute myeloid leukemia (AML) is a hematologic malignancy that most frequently develops in older adults. Overall, AML is associated with a high mortality although advancements in genetic risk stratification and new treatments are leading to improvements in outcomes for some subgroups. In this review, we discuss an individualized approach to intensive therapy with a focus on the role of recently approved novel therapies as well as the selection of post-remission therapies for patients in first remission. We discuss the management of patients with relapsed and refractory AML, including the role of targeted treatment and allogeneic stem cell transplant. Next, we review non-intensive treatment for older and unfit AML patients including the use of azacitidine and venetoclax. Finally, we discuss the integration of palliative care in the management of patients with AML.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.898
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0050.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0010.000

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 head0.211
GPT teacher head0.512
Teacher spread0.300 · 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