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Current Treatment of Chronic Myeloid Leukemia

2001· article· en· W2471352820 on OpenAlexafffund
Diane Coso, Armand Keating

Bibliographic record

VenueHematology · 2001
Typearticle
Languageen
FieldMedicine
TopicChronic Myeloid Leukemia Treatments
Canadian institutionsPrincess Margaret Cancer CentreUniversity Health Network
FundersFondation de FranceUniversity of TorontoUniversity Health Network
KeywordsMyeloid leukemiaMedicineTyrosine-kinase inhibitorMalignancyTransplantationDiseaseHematopoietic stem cell transplantationHematopoietic cellImmunologyMyeloidTyrosine kinaseCancer researchTargeted therapyHaematopoiesisInternal medicineStem cellBiologyCancer

Abstract

fetched live from OpenAlex

We are entering an exciting era in the management of chronic myeloid leukemia (CML). This, in part is related to our considerable understanding of the molecular lesion associated with the disease-arguably the best characterized of any malignancy. Although allogeneic hematopoietic cell transplantation remains the sole potentially curative therapy at present, newer agents such as the tyrosine kinase inhibitor STI571 show promise and may eventually replace less specific cytotoxic therapy. This review focuses on the numerous options currently available for treating CML and includes a treatment algorithm.

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 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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.745
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.027
GPT teacher head0.310
Teacher spread0.283 · 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 teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

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

Citations1
Published2001
Admission routes2
Has abstractyes

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