Considerations for the Impact of Personal Genome Information: A Study of Genomic Profiling among Genetics and Genomics Professionals
Bibliographic record
Abstract
With the expansion of genomic-based clinical applications, it is important to consider the potential impact of this information particularly in terms of how it may be interpreted and applied to personal perceptions of health. As an initial step to exploring this question, we conducted a study to gain insight into potential psychosocial and health motivations for, as well as impact associated with, undergoing testing and disclosure of individual "variomes" (catalogue of genetic variations). To enable the collection of fully informed opinions, 14 participants with advanced training in genetics underwent whole-genome profiling and received individual reports of estimated genomic ancestry, genotype data and reported disease associations. Emotional, cognitive and health behavioral impact was assessed through one-on-one interviews and questionnaires administered pre-testing and 1-week and 3-months post-testing. Notwithstanding the educational and professional bias of our study population, the results identify several areas of research for consideration within additional populations. With the development of new and less costly approaches to genome risk profiling, now available for purchase direct-to-consumers, it is essential that genome science research be conducted in parallel with studies assessing the societal and policy implications of genome information for personal use.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".