Globalizing Genomics: The Origins of the International Nucleotide Sequence Database Collaboration
Bibliographic record
Abstract
Genomics is increasingly considered a global enterprise - the fact that biological information can flow rapidly around the planet is taken to be important to what genomics is and what it can achieve. However, the large-scale international circulation of nucleotide sequence information did not begin with the Human Genome Project. Efforts to formalize and institutionalize the circulation of sequence information emerged concurrently with the development of centralized facilities for collecting that information. That is, the very first databases build for collecting and sharing DNA sequence information were, from their outset, international collaborative enterprises. This paper describes the origins of the International Nucleotide Sequence Database Collaboration between GenBank in the United States, the European Molecular Biology Laboratory Databank, and the DNA Database of Japan. The technical and social groundwork for the international exchange of nucleotide sequences created the conditions of possibility for imagining nucleotide sequences (and subsequently genomes) as a "global" objects. The "transnationalism" of nucleotide sequence was critical to their ontology - what DNA sequences came to be during the Human Genome Project was deeply influenced by international exchange.
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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 | 0.020 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.006 | 0.019 |
| Scholarly communication | 0.015 | 0.018 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".