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Record W3038581931 · doi:10.14740/jmc3510

Therapeutic Challenges in Chronic Myeloid Leukemia: A Case-Based Discussion

2020· article· en· W3038581931 on OpenAlexvenueno aff
Ariel Perez Perez, Grant Jester, Yehuda Galili, Ahmad El-Far, Said Baidas

Bibliographic record

VenueJournal of Medical Cases · 2020
Typearticle
Languageen
FieldMedicine
TopicChronic Myeloid Leukemia Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineMyeloid leukemiaMyeloproliferative neoplasmChromosomal translocationTyrosine kinaseRefractory (planetary science)Philadelphia chromosomebreakpoint cluster regionCancer researchTyrosine-kinase inhibitorMyeloidOncologyInternal medicineMyelofibrosisGeneBone marrowGeneticsReceptorCancerBiology

Abstract

fetched live from OpenAlex

Chronic myeloid leukemia (CML) is a myeloproliferative neoplasm characterized by a reciprocal translocation between the long arms of chromosomes 9 and 22 that results in expression of the oncoprotein BCR-ABL1. An optimal response to tyrosine kinase inhibitors (TKIs) requires a BCR-ABL transcript level ≤ 10% at 3 months, ≤ 1% at 6 months, ≤ 0.1% at 1 year, and ≤ 0.01% onwards. Complex scenarios like P190 BCR-ABL CML, unusual BCR-ABL transcripts, primary refractory CML, and detection of TKI-resistance mutations during treatment frequently pose a therapeutic challenge. In this article we present some of these clinical scenarios using a case-based approach. J Med Cases. 2020;11(7):215-220 doi: https://doi.org/10.14740/jmc3510

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)0.001
metaresearch head score (Gemma)0.001
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: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.450
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.081
GPT teacher head0.330
Teacher spread0.249 · 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 designCase report
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

Citations4
Published2020
Admission routes1
Has abstractyes

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