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Record W4311679896 · doi:10.1182/hematology.2022000357

Clinical screening for Ph-like ALL and the developing role of TKIs

2022· article· en· W4311679896 on OpenAlexaff
Thai Hoa Tran, Sarah K. Tasian

Bibliographic record

VenueHematology · 2022
Typearticle
Languageen
FieldMedicine
TopicAcute Lymphoblastic Leukemia research
Canadian institutionsUniversité de MontréalCentre Hospitalier Universitaire Sainte-Justine
FundersNational Cancer Institute
KeywordsMinimal residual diseaseABLImmunotherapyMedicineCancer researchLymphoblastic LeukemiaAcute lymphocytic leukemiaDiseaseLineage (genetic)ImmunologyLeukemiaGeneBiologyOncologyInternal medicineReceptorGeneticsImmune systemTyrosine kinase

Abstract

fetched live from OpenAlex

Philadelphia chromosome-like acute lymphoblastic leukemia (Ph-like ALL) is a common subtype of B-lineage acute lymphoblastic leukemia (B-ALL) with increasing frequency across the age spectrum. Characterized by a kinase-activated gene expression profile and driven by a variety of genetic alterations involving cytokine receptors and kinases, Ph-like ALL is associated with high rates of residual disease and relapse in patients treated with conventional chemotherapy. In this case-based review, we describe the biology of the 2 major ABL-class and JAK pathway genetic subtypes of Ph-like ALL, discuss current diagnostic testing methodologies, and highlight targeted inhibitor and chemo/immunotherapy approaches under clinical investigation in children, adolescents, and adults with these high-risk leukemias.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
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 head0.055
GPT teacher head0.377
Teacher spread0.322 · 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

Citations24
Published2022
Admission routes1
Has abstractyes

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