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Record W4392588545 · doi:10.1016/j.gimo.2024.101734

P823: Insights and strategies for inclusive adolescent and young adult participation in genetics research

2024· article· en· W4392588545 on OpenAlexaff
Tasha Wainstein, Courtney B. Cook, Daniel Assamad, Julia Heaton, M. S. Randhawa, David T. Yeung, Lauren Jennings, Robin Z. Hayeems, Harpreet Chhina, Anthony Cooper, GenCOUNSEL. Study, Jehannine Austin, Alison M. Elliott

Bibliographic record

VenueGenetics in Medicine Open · 2024
Typearticle
Languageen
FieldHealth Professions
TopicHealth Policy Implementation Science
Canadian institutionsUniversity of TorontoUniversity of British Columbia
Fundersnot available
KeywordsPsychologyDevelopmental psychologyGeneticsBiology

Abstract

fetched live from OpenAlex

Adolescents and young adults (AYA) constitute a rapidly growing population group whose health concerns are gaining recognition throughout health care. There is growing appreciation of the need to involve AYA in all matters affecting their lives, including their participation in research. Yet, they infrequently participate in research that focuses on their experiences of genetic counseling and testing. This may stem from entrenched perspectives about challenges of conducting AYA research. We aimed to provide guidance about engaging AYA in research, based on a review of our experiences conducting studies of this nature.

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)0.129
metaresearch head score (Gemma)0.091
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesOpen science
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.995
Threshold uncertainty score0.682

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1290.091
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0260.039
Scholarly communication0.0200.025
Open science0.0050.040
Research integrity0.0160.023
Insufficient payload (model declined to judge)0.0090.002

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 head0.698
GPT teacher head0.750
Teacher spread0.051 · 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.

Study designQualitative
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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