Whole Genome Sequencing as a Diagnostic Test: Challenges and Opportunities
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
BACKGROUND: Extraordinary technological advances and decreases in the cost of DNA sequencing have made the possibility of whole genome sequencing (WGS) as a highly accessible clinical test for numerous indications feasible. There have been many recent, successful applications of WGS in establishing the etiology of complex diseases and guiding therapeutic decision-making in neoplastic and nonneoplastic diseases and in various aspects of reproductive health. However, there are major, but not insurmountable, obstacles to the increased clinical implementation of WGS, such as hidden costs, issues surrounding sequencing and analysis, quality assurance and standardization protocols, ethical dilemmas, and difficulties with interpretation of the results. CONTENT: The widespread use of WGS in routine clinical practice remains a distant proposition. Prospective trials will be needed to establish if, and for whom, the benefits of WGS will outweigh the likely substantial costs associated with follow-up tests, the risks of overdiagnosis and overtreatment, and the associated emotional distress. SUMMARY: WGS should be carefully implemented in the clinic to allow the realization of its potential to improve patient health in specific indications. To minimize harm the use of WGS for all other reasons must be carefully evaluated before clinical implementation.
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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 | 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 it