Sustaining large-scale infrastructure to promote pre-competitive biomedical research: lessons from mouse genomics
Bibliographic record
Abstract
Bio-repositories and databases for biomedical research enable the efficient community-wide sharing of reagents and data. These archives play an increasingly prominent role in the generation and dissemination of bioresources and data essential for fundamental and translational research. Evidence suggests, however, that current funding and governance models, generally short-term and nationally focused, do not adequately support the role of archives in long-term, transnational endeavours to make and share high-impact resources. Our qualitative case study of the International Knockout Mouse Consortium and the International Mouse Phenotyping Consortium examines new governance mechanisms for archive sustainability. Funders and archive managers highlight in interviews that archives need stable public funding and new revenue-generation models to be sustainable. Sustainability also requires archives, journal publishers, and funders to implement appropriate incentives, associated metrics, and enforcement mechanisms to ensure that researchers use archives to deposit reagents and data to make them publicly accessible for academia and industry alike.
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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 | 0.029 | 0.036 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.012 |
| Scholarly communication | 0.010 | 0.013 |
| Open science | 0.003 | 0.011 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".