Evolutionary concepts in biobanking - the BC BioLibrary
Bibliographic record
Abstract
BACKGROUND: Medical research to improve health care faces a major problem in the relatively limited availability of adequately annotated and collected biospecimens. This limitation is creating a growing gap between the pace of scientific advances and successful exploitation of this knowledge. Biobanks are an important conduit for transfer of biospecimens (tissues, blood, body fluids) and related health data to research. They have evolved outside of the historical source of tissue biospecimens, clinical pathology archives. Research biobanks have developed advanced standards, protocols, databases, and mechanisms to interface with researchers seeking biospecimens. However, biobanks are often limited in their capacity and ability to ensure quality in the face of increasing demand. Our strategy to enhance both capacity and quality in research biobanking is to create a new framework that repatriates the activity of biospecimen accrual for biobanks to clinical pathology. METHODS: The British Columbia (BC) BioLibrary is a framework to maximize the accrual of high-quality, annotated biospecimens into biobanks. The BC BioLibrary design primarily encompasses: 1) specialized biospecimen collection units embedded within clinical pathology and linked to a biospecimen distribution system that serves biobanks; 2) a systematic process to connect potential donors with biobanks, and to connect biobanks with consented biospecimens; and 3) interdisciplinary governance and oversight informed by public opinion. RESULTS: The BC BioLibrary has been embraced by biobanking leaders and translational researchers throughout BC, across multiple health authorities, institutions, and disciplines. An initial pilot network of three Biospecimen Collection Units has been successfully established. In addition, two public deliberation events have been held to obtain input from the public on the BioLibrary and on issues including consent, collection of biospecimens and governance. CONCLUSION: The BC BioLibrary framework addresses common issues for clinical pathology, biobanking, and translational research across multiple institutions and clinical and research domains. We anticipate that our framework will lead to enhanced biospecimen accrual capacity and quality, reduced competition between biobanks, and a transparent process for donors that enhances public trust in biobanking.
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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 | 0.026 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.008 | 0.032 |
| Scholarly communication | 0.014 | 0.008 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".