MétaCan
Menu
Back to cohort
Record W2158017562 · doi:10.1177/0115426505020004377

A Multidisciplinary Review of Nutrition Considerations in the Pediatric Oncology Population: A Perspective From Children's Oncology Group

2005· review· en· W2158017562 on OpenAlexaff
Elena J. Ladas, Nancy Sacks, Lillian R. Meacham, Lori Enriquez, Genevieve Lowry, R. Hawkes, Gaye Dadd, Paul Rogers

Bibliographic record

VenueNutrition in Clinical Practice · 2005
Typereview
Languageen
FieldMedicine
TopicChildhood Cancer Survivors' Quality of Life
Canadian institutionsBC Children's Hospital
Fundersnot available
KeywordsMedicinePsychosocialMultidisciplinary approachPediatric oncologyQuality of life (healthcare)Intensive care medicineCancerChildhood cancerClinical PracticeClinical OncologyOncology nursingPopulationFamily medicineInternal medicineNursingPsychiatryEnvironmental health

Abstract

fetched live from OpenAlex

Over the past few decades, great progress has been made in the survival rates of childhood cancer. As survival rates have improved, there has been an increased focus on supportive care. Nutrition is a supportive-care modality that has been associated with improved tolerance to chemotherapy, improved survival, increased quality of life, and decreased risk of infection in children undergoing anticancer therapy. Guidelines and assessment criteria have been proposed for the nutrition management of a child with cancer; however, there is no consistent use of criteria among institutions treating children with cancer. This review will present the current evidence and standards of practice incorporating aspects of nutrition, nursing, pharmacology, and psychosocial challenges to consider in the nutrition management of a child with cancer. Recommendations for clinical practice are presented.

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)0.003
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 score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0040.006
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.175
GPT teacher head0.551
Teacher spread0.376 · 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

Citations177
Published2005
Admission routes1
Has abstractyes

Explore more

Same venueNutrition in Clinical PracticeSame topicChildhood Cancer Survivors' Quality of LifeFrench-language works237,207