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Record W2414413276 · doi:10.1097/cco.0000000000000193

Social competence in pediatric brain tumor survivors

2015· review· en· W2414413276 on OpenAlexaff
Fiona Schulte

Bibliographic record

VenueCurrent Opinion in Oncology · 2015
Typereview
Languageen
FieldMedicine
TopicChildhood Cancer Survivors' Quality of Life
Canadian institutionsAlberta Children's Hospital
Fundersnot available
KeywordsOperationalizationSocial competenceCompetence (human resources)Conceptual frameworkMedicinePopulationDevelopmental psychologyPsychologySocial changeSocial psychologySocial scienceSociologyEnvironmental health

Abstract

fetched live from OpenAlex

PURPOSE OF REVIEW: The purpose of this article is to review the literature in the area of social competence in pediatric brain tumor survivors published in the last year. RECENT FINDINGS: Research published over the past year examining the social competence of pediatric brain tumor survivors has seen the consistent application of a comprehensive conceptual framework that pertains specifically to children with brain disorders. Subsequent to the application of a comprehensive conceptual framework, more sophisticated research approaches have begun to advance our understanding of deficits among this population. Specifically, operationalization of social competence is evolving. SUMMARY: Continued application of a conceptual framework and investigation into the components that comprise the framework will enhance the depth of our understanding of social competence deficits among this population. Research must continue to use innovative approaches to measuring social competence. Considerable gaps still exist with respect to identifying risk and resilience factors for social competence deficits.

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)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.227
GPT teacher head0.504
Teacher spread0.277 · 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 designSystematic review
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

Citations18
Published2015
Admission routes1
Has abstractyes

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