Cultivating DNA Sequencing Technology After the Human Genome Project
Bibliographic record
Abstract
When the Human Genome Project was completed in 2003, automated Sanger DNA sequencing with fluorescent dye labels was the dominant technology. Several nascent alternative methods based on older ideas that had not been fully developed were the focus of technical researchers and companies. Funding agencies recognized the dynamic nature of technology development and that, beyond the Human Genome Project, there were growing opportunities to deploy DNA sequencing in biological research. Consequently, the National Human Genome Research Institute of the National Institutes of Health created a program-widely known as the Advanced Sequencing Technology Program-that stimulated all stages of development of new DNA sequencing methods, from innovation to advanced manufacturing and production testing, with the goal of reducing the cost of sequencing a human genome first to $100,000 and then to $1,000. The events of this period provide a powerful example of how judicious funding of academic and commercial partners can rapidly advance core technology developments that lead to profound advances across the scientific landscape.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.003 | 0.004 |
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".