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Feasibility of Utilizing a Brief Cognitive Battery in Three-Year-Old Patients During Treatment for Acute Lymphoblastic Leukemia

2024· preprint· en· W4402011980 on OpenAlexaff
Sameera Ramjan, Peter D. Cole, Melanie Blair Thies, Lewis B. Silverman, A.M. Frederickson, Adrian Schembri, Jennifer Welch, Justine M. Kahn, Kara M. Kelly, Thai Hoa Tran, Bruno Michon, Lisa Gennarini, Stephen A. Sands

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldMedicine
TopicChildhood Cancer Survivors' Quality of Life
Canadian institutionsUniversité LavalCentre hospitalier universitaire de QuébecCentre Hospitalier Universitaire Sainte-Justine
FundersNational Cancer InstituteNational Institutes of Health
KeywordsNeurocognitiveLymphoblastic LeukemiaMedicineCognitionPediatricsLeukemiaOncologyInternal medicinePsychiatry

Abstract

fetched live from OpenAlex

Treatment of Acute Lymphoblastic Leukemia is associated with neurocognitive deficits in young children. While computerized measures have been utilized in pediatric oncology research, they exclude patients below the age of 4 years old. Patients enrolled on “Treatment of Newly Diagnosed Acute Lymphoblastic Leukemia in Children and Adolescents” were offered participation in an optional cognitive study. Three-year old patients did not differ from four-year old patients on their ability to complete tests or perform tests. Including patients diagnosed at age 3 will serve to improve our understanding of at-risk patients and the cognitive trajectory of this age group both during treatment.

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)0.005
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 score0.008
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
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 head0.054
GPT teacher head0.348
Teacher spread0.294 · 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
Published2024
Admission routes1
Has abstractyes

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