A New Twist on an Old Problem: Primary Care Physicians and Results From Direct-to-consumer Genetic Testing
Bibliographic record
Abstract
With the costs of genomic and genetic testing rapidly decreasing, private companies have begun to offer consumers, including minors, the opportunity to receive a genetic analysis of their DNA. The availability of direct-to-consumer genetic testing (DTC-GT) will inevitably result in patients approaching their healthcare providers for interpretation of results, referrals for follow-up tests or provision of personalized medicine. As most healthcare systems require a referral for access to a specialist, the patients are likely to approach primary care providers. The issue of what the professional obligations are for the primary care physician in the case where they did not order the test is not new. The growing DTC-GT movement will add a 'new twist to an old problem.' Best practice recommendations regarding the value of DTC-GT, as well as the identification of current ethical, legal and social implications are urgently needed.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.077 | 0.217 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.005 | 0.041 |
| Scholarly communication | 0.014 | 0.036 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.019 | 0.026 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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.
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 source (direct Gemma or distilled Codex), 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".