MétaCan
Menu
Back to cohort
Record W1883095706 · doi:10.1111/jlme.12288

Returning a Research Participant's Genomic Results to Relatives: Analysis and Recommendations

2015· article· en· W1883095706 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueThe Journal of Law Medicine & Ethics · 2015
Typearticle
Languageen
FieldMedicine
TopicEthics in Clinical Research
Canadian institutionsDalhousie University
FundersEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentNational Cancer InstituteNational Human Genome Research InstituteWellcome Trust
KeywordsParticipant observationPsychologySocial psychologySociologySocial science

Abstract

fetched live from OpenAlex

The debate about how to manage individual research results and incidental findings in genetic and genomic research has focused primarily on what information, if any, to offer back to research participants. However, increasing controversy surrounds the question of whether researchers have any responsibility to offer a participant’s results (defined here to include both individual research results and incidental findings) to the participant’s relatives, including after the participant’s death. This question arises in multiple contexts, including when researchers discover a result with potentially important health implications for genetic relatives, when a participant’s relatives ask a researcher whether any research results about the participant have implications for their own health or reproductive planning, when a participant’s relative asks whether any of the participant’s results have implications for a child’s health, and when the participant is deceased and the participant’s relatives seek information about the participant’s genetic results in order to address their own health or reproductive concerns.

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.

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmaResearch integrity
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Theoretical or conceptualhigh
gptno category
Domain: not available · Genre: Commentary
About the Canadian research system: no · About a Canadian topic: no
Theoretical or conceptuallow
models splitAgreement compares identical category sets and study designs across arms.

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)0.167
metaresearch head score (Gemma)0.272
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Research integrity
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.712
Threshold uncertainty score0.989

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.1670.272
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.014
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 head0.909
GPT teacher head0.697
Teacher spread0.212 · 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