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Record W2161013848 · doi:10.1002/pbc.24508

Guideline for the prevention of acute nausea and vomiting due to antineoplastic medication in pediatric cancer patients

2013· article· en· W2161013848 on OpenAlexafffund
L. Lee Dupuis, Sabrina Boodhan, Mark T. Holdsworth, Paula D. Robinson, Richard Hain, Carol Portwine, Erin O’Shaughnessy, Lillian Sung

Bibliographic record

VenuePediatric Blood & Cancer · 2013
Typearticle
Languageen
FieldMedicine
TopicNausea and vomiting management
Canadian institutionsMcMaster UniversityUniversity of TorontoSickKids FoundationPediatric Oncology GroupChildren's Hospital of Eastern OntarioInstitute for Clinical Evaluative SciencesHospital for Sick Children
FundersCanadian Institutes of Health ResearchPediatric Oncology Group of Ontario
KeywordsMedicineAntiemeticGuidelineNauseaVomitingAprepitantIntensive care medicinePsychological interventionCancerPediatric cancerAnesthesiaInternal medicinePsychiatry

Abstract

fetched live from OpenAlex

This guideline provides an approach to the prevention of acute antineoplastic-induced nausea and vomiting (AINV) in children. It was developed by an international, inter-professional panel using AGREE and CAN-IMPLEMENT methods. Evidence-based interventions that provide optimal AINV control in children receiving antineoplastic agents of high, moderate, low, and minimal emetogenicity are recommended. Recommendations are also made regarding selection of antiemetic agents for children who are unable to receive corticosteroids for AINV control, the role of aprepitant and optimal doses of antiemetic agents. Gaps in the evidence used to support the recommendations were identified. The contribution of this guideline to AINV control in children requires prospective evaluation.

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)0.003
metaresearch head score (Gemma)0.012
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: Not applicable
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.030
Threshold uncertainty score0.060

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.012
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.003
Bibliometrics0.0020.002
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0030.001
Research integrity0.0040.006
Insufficient payload (model declined to judge)0.0050.003

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 head0.012
GPT teacher head0.301
Teacher spread0.288 · 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
GenreMethods

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

Citations147
Published2013
Admission routes2
Has abstractyes

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