In conversation with Lori Passmore
Bibliographic record
Abstract
Lori Passmore is a Group Leader at the MRC Laboratory of Molecular Biology (MRC-LMB). She studied Biochemistry at the University of British Columbia in Vancouver (Canada), before moving to the UK in 1999 for a PhD at the Institute of Cancer Research. After completing her PhD, Lori moved to Cambridge, where she became a Post-Doctoral Fellow at the MRC-LMB. In 2009, Lori started her own group at the MRC-LMB and was subsequently awarded an ERC Starting Grant (2011), an ERC Consolidator Grant (2017) and a Wellcome Discovery Award (2023). She was also elected into the EMBO Young Investigator Programme (2015) and EMBO Membership (2018). Lori's research focusses on the determination of the structures of protein complexes that regulate gene expression, using primarily cryo-electron microscopy and in vitro assays. Her work has contributed significantly to our understanding of the underlying molecular mechanisms of cellular processes, giving insights into human physiology and disease. In this interview, Lori provides an overview of her research and discusses current challenges in the field, recalls the key events and collaborations that have helped shape her successful research career and offers advice to early career scientists.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| 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 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".