A European Survey on Biobanks: Trends and Issues
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
Biobanks have recently gained great significance for research and personalised medicine, being recognised as a crucial infrastructure. At the same time, the widely varied practices in biobanking may also pose a barrier to cross-border research and collaboration by limiting access to samples and data. Nevertheless, the extent of the actual activities and the impact of the level of networking and harmonisation have not been fully assessed. To address these issues and to obtain missing knowledge on the extent of biobanking in Europe, the Institute for Prospective Technological Studies (IPTS) of the European Commission's Joint Research Centre, in collaboration with the European Science and Technology Observatory (ESTO), conducted a survey among European biobanks. In total, 126 biobanks from 23 countries responded to the survey. Most of them are small or medium-sized public collections set up either for population-based or disease-specific research purposes. The survey indicated a limited networking among the infrastructures. The large majority of them are stand-alone collections and only about half indicated to have a policy for cross-border sharing of samples. Yet, scientific collaborations based on the use of each biobank appear to be prominent. Significant variability was found in terms of consent requirements and related procedures as well as for privacy and data protection issues among the biobanks surveyed. To help promote networking of biobanks and thus maximise public health benefits, at least some degree of harmonisation should be achieved.
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 | 0.021 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 | 0.002 |
| 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