The Challenge of Informed Consent and Return of Results in Translational Genomics: Empirical Analysis and Recommendations
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.
Bibliographic record
Abstract
Large-scale sequencing tests, including whole-exome and whole-genome sequencing (WES/WGS), are rapidly moving into clinical use. Sequencing is already being used clinically to identify therapeutic opportunities for cancer patients who have run out of conventional treatment options, to help diagnose children with puzzling neurodevelopmental conditions, and to clarify appropriate drug choices and dosing in individuals. To evaluate and support clinical applications of these technologies, the National Human Genome Research Institute (NHGRI) and National Cancer Institute (NCI) have funded studies on clinical and research sequencing under the Clinical Sequencing Exploratory Research (CSER) program as well as studies on return of results (RoR). Most of these studies use sequencing in real-world clinical settings and collect data on both the application of sequencing and the impact of receiving genomic findings on study participants. They are occurring in the context of controversy over how to obtain consent for exome and genome sequencing.
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.
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.037 | 0.062 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.003 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it