Mitochondria and Us: from exploration to global collective
Bibliographic record
Abstract
The ‘Mitochondria and Us’ project embodies our ambition to break new ground by working across traditionally siloed disciplines and by co-creating innovative approaches to impact research and societal awareness. Our vision is to provide a paradigm shift of knowledge integration at all levels adopting a pandisciplinary cooperation in a crucial and emerging area of medicine impacting several incurable human diseases. We describe our efforts on this journey through a series of ‘Crossover’ workshops and webinars supported by the Biochemical Society and the Royal Society of Edinburgh, by bringing together mitochondria experts from the University of Glasgow and the University of Toronto together with designers from the Innovation School of the Glasgow School of Art, artists, patient groups, social scientists and bioethicists. The global Mitochondria Collective initiative has the vision to unite research, community voices and stakeholders to bring mitochondria to the forefront of medicine as a means of sustained impact on improved healthcare and quality of life.
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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 | 0.018 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.013 | 0.034 |
| Scholarly communication | 0.019 | 0.026 |
| Open science | 0.002 | 0.042 |
| Research integrity | 0.006 | 0.008 |
| Insufficient payload (model declined to judge) | 0.017 | 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".