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Record W2956168677 · doi:10.1182/blood.2019000239

Combining gene mutation with gene expression analysis improves outcome prediction in acute promyelocytic leukemia

2019· article· en· W2956168677 on OpenAlexaff
Antonio R. Lucena‐Araujo, Juan Luiz Coelho‐Silva, Diego A. Pereira‐Martins, Douglas RA Silveira, Luisa C A Koury, Raul Antônio Morais Melo, Rosane Bittencourt, Kátia Bórgia Barbosa Pagnano, Ricardo Pasqüini, Elenaide C. Nunes, Evandro M. Fagundes, Ana Glória, Fábio R. Kerbauy, Maria de Lourdes Chauffaille, Israel Bendit, Vanderson Rocha, Armand Keating, Martin S. Tallman, Raul C. Ribeiro, Richard Dillon, Arnold Ganser, Bob Löwenberg, Peter J.M. Valk, Francesco Lo‐Coco, Miguel Á. Sanz, Nancy Berliner, Eduardo Magalhães Rego

Bibliographic record

VenueBlood · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRetinoids in leukemia and cellular processes
Canadian institutionsPrincess Margaret Cancer Centre
FundersNational Cancer InstituteFundação de Amparo à Pesquisa do Estado de São PauloConselho Nacional de Desenvolvimento Científico e TecnológicoAmerican Society of Hematology
KeywordsAcute promyelocytic leukemiaMyeloid leukemiaAnthracyclineOncologyMedicineRetinoic acidInternal medicineMutationTretinoinDaunorubicinGeneLeukemiaMalignancyCancer researchBioinformaticsGeneticsBiologyCancer

Abstract

fetched live from OpenAlex

Abstract Luceno-Araujo et al use assays of mutations associated with myeloid malignancy to propose an integrative prognostic score for acute promyelocytic leukemia (ISAPL) in patients treated with all-trans retinoic acid and anthracycline-based therapy. They demonstrate that the ISAPL is superior for predicting outcomes and identifying patients who may benefit from alternative therapies to maximize their chance of a cure.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.174
Threshold uncertainty score0.570

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0000.000

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 head0.005
GPT teacher head0.220
Teacher spread0.215 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations25
Published2019
Admission routes1
Has abstractyes

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