BRAIN UK: Accessing NHS tissue archives for neuroscience research
Bibliographic record
Abstract
The purpose of BRAIN UK (the UK BRain Archive Information Network) is to make the very extensive and comprehensive National Health Service (NHS) Neuropathology archives available to the national and international neuroscience research community. The archives comprise samples of tumours and a wide range of other neurological disorders, not only from the brain but also spinal cord, peripheral nerve, muscle, eye and other organs when relevant. BRAIN UK was founded after the recognition of the importance of this large tissue resource, which was not previously readily accessible for research use. BRAIN UK has successfully engaged the majority of the regional clinical neuroscience centres in the United Kingdom to produce a centralised database of the extensive autopsy and biopsy archive. Together with a simple application process and its broad ethical approval, BRAIN UK offers researchers easy access to most of the national archives of neurological tissues and tumours (http://www.brain-uk.org). The range of tissues available reflects the spectrum of disease in society, including many conditions not covered by disease-specific brain banks, and also allows relatively large numbers of cases of uncommon conditions to be studied. BRAIN UK has supported 141 studies (2010-2020) that have generated 70 publications employing methodology as diverse as morphometrics, genetics, proteomics and methylomics. Tissue samples that would otherwise have been unused have supported valuable neuroscience research. The importance of this unique resource will only increase as molecular techniques applicable to human tissues continue to develop and technical advances permit large-scale high-throughput studies.
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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 | 0.010 | 0.041 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.192 | 0.163 |
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".