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Record W2115740244 · doi:10.1586/ehm.10.68

Older patients with acute myeloid leukemia

2010· review· en· W2115740244 on OpenAlexaff
Karen Yee, Armand Keating

Bibliographic record

VenueExpert Review of Hematology · 2010
Typereview
Languageen
FieldMedicine
TopicAcute Myeloid Leukemia Research
Canadian institutionsPrincess Margaret Cancer CentreUniversity Health Network
Fundersnot available
KeywordsMedicineMyeloid leukemiaDiseaseOncologyTolerabilityInduction chemotherapyClinical trialInternal medicineChemotherapyIntensive care medicineAdverse effect

Abstract

fetched live from OpenAlex

Outcomes for older patients with acute myeloid leukemia have not improved over the last three decades, with only a small proportion of patients achieving long-term disease-free survival with standard induction chemotherapy. Older patients are more likely to have comorbidities, diminished functional reserve and other age-related issues, which decrease their tolerability to chemotherapy. Furthermore, the disease is frequently associated with poor-risk features, such as unfavorable cytogenetic abnormalities, antecedent hematologic disorders and expression of the multidrug resistant P-glycoprotein, which are associated with chemoresistant disease. Therefore, is it not only important to develop newer treatment modalities, but also to develop and validate prognostic models to help select the patients who are likely to benefit from and be suitable for intensive therapy, and reproducibly risk-stratify (based on disease biology) a relatively uniform group of older patients onto trials, so that the clinical significance of new therapeutic agents can be evaluated.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.002

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.

Opus teacher head0.020
GPT teacher head0.364
Teacher spread0.344 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations4
Published2010
Admission routes1
Has abstractyes

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