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Record W4324116807 · doi:10.1016/j.gimo.2023.100108

P089: Genetic, pharmacogenetics and outcomes in a cohort of pediatric acute myeloid leukemia patients in two reference centers from Colombia

2023· article· en· W4324116807 on OpenAlexaff
Luz Yunis, Adriana Linares, Gisela Barros, Johnny J. Garcia, Nelson Aponte, Laura Niño Torres, Gloria Uribe, Edna Quintero, Jaime A. Moreno, Leila Martínez, Juan J. Yunis

Bibliographic record

VenueGenetics in Medicine Open · 2023
Typearticle
Languageen
FieldMedicine
TopicAcute Myeloid Leukemia Research
Canadian institutionsMisericordia Community Hospital
Fundersnot available
KeywordsPharmacogeneticsMyeloid leukemiaCohortMedicinePediatricsOncologyInternal medicineGeneticsGenotypeBiologyGene

Abstract

fetched live from OpenAlex

In Pediatric patients, acute lymphoid leukemia (ALL) is the most frequent type of acute leukemia with a very good prognosis, while acute myeloid leukemia (AML) has a lower incidence and generally poor prognosis. Very few studies have been carried out to characterize AML pediatric patients in Latin American populations. In this study, we described and correlated genetic and pharmacogenetic variants with clinical characteristics and outcomes in a cohort of pediatric patients with de novo AML at two pediatric cancer centers from Bogotá, Colombia.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.102
Threshold uncertainty score0.203

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
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 head0.042
GPT teacher head0.384
Teacher spread0.342 · 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 designObservational
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

Citations0
Published2023
Admission routes1
Has abstractyes

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