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Record W4376139173 · doi:10.1002/jha2.697

SARS‐CoV‐2 infections in patients enrolled on the Children's Oncology Group standard‐risk B‐cell acute lymphoblastic leukemia trial, AALL1731

2023· article· en· W4376139173 on OpenAlexaff
Caitlin W. Elgarten, John A. Kairalla, Joel Thompson, Tamara P. Miller, Cindy Wang, Susan J. Conway, Mignon L. Loh, Elizabeth A. Raetz, Sumit Gupta, Rachel E. Rau, Anne Angiolillo, Karen R. Rabin, Sarah Alexander

Bibliographic record

VenueeJHaem · 2023
Typearticle
Languageen
FieldMedicine
TopicCOVID-19 and healthcare impacts
Canadian institutionsHospital for Sick Children
FundersNational Institutes of HealthNational Cancer InstituteNational Heart, Lung, and Blood InstituteSt. Baldrick's Foundation
KeywordsMedicineInternal medicineLeukemiaAsymptomaticLymphomaLymphoblastic LeukemiaLymphoblastic lymphomaDiseaseAdverse effectOncologyPediatricsImmunologyT cell

Abstract

fetched live from OpenAlex

Hematologic malignancy is a risk factor for severe coronavirus disease 2019 (COVID-19) in adults; however, data specific to children with leukemia are limited. High-quality infectious adverse event data from the ongoing Children's Oncology Group (COG) standard-risk B acute lymphoblastic leukemia/lymphoma (ALL/LLy) trial, AALL1731, were analyzed to provide a disease-specific estimate of SARS-CoV-2 infection outcomes in pediatric ALL. Of 253 patients with reported infections, the majority (77.1%) were asymptomatic or mildly symptomatic (CTCAE grade 1/2) and there was a single COVID-19-related death. These data suggest SARS-CoV-2 infection does not confer substantial morbidity among young patients with B-lymphoblastic leukemia/lymphoma (B-ALL/LLy).

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.031
GPT teacher head0.352
Teacher spread0.321 · 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

Citations5
Published2023
Admission routes1
Has abstractyes

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