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Record W3125779445 · doi:10.3390/curroncol28010061

Advancing the Field of Pediatric Exercise Oncology: Research and Innovation Needs

2021· review· en· W3125779445 on OpenAlexaffvenue
Amanda Wurz, Emma McLaughlin, Carolina Chamorro-Viña, Sarah L. Grimshaw, Lotta Hamari, Miriam Götte, Sabine Kesting, Francesca Rossi, Patrick van der Torre, Gregory M.T. Guilcher, Krista McIntyre, S. Nicole Culos‐Reed

Bibliographic record

VenueCurrent Oncology · 2021
Typereview
Languageen
FieldMedicine
TopicChildhood Cancer Survivors' Quality of Life
Canadian institutionsAlberta Children's HospitalAlberta Cancer FoundationUniversity of Calgary
Fundersnot available
KeywordsMedicinePhysical activityPediatric oncologyField (mathematics)Medical educationCancerPhysical therapyInternal medicine

Abstract

fetched live from OpenAlex

The field of pediatric exercise oncology explores the relationships between physical activity (PA), including exercise, and a range of outcomes among children and adolescents affected by cancer. Although PA is safe and beneficial for this population, several important gaps in knowledge and practice remain. In this article, we describe research and innovation needs that were developed with a team of international experts and relevant literature, a series of online surveys, and an in-person meeting. Addressing these needs will contribute valuable knowledge and practice outputs to advance this field, ultimately enabling a greater number of children and adolescents affected by cancer to realize the benefits of moving more.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation 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 score0.944
Threshold uncertainty score0.985

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.000
Bibliometrics0.0020.004
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0000.000

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 head0.330
GPT teacher head0.575
Teacher spread0.245 · 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 teacher head, 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

Citations33
Published2021
Admission routes2
Has abstractyes

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