Spotlight on early-career researchers: an interview with Alexander Wyatt
Bibliographic record
Abstract
Dr. Alexander Wyatt is a Senior Research Scientist at the Vancouver Prostate Centre and Assistant Professor at the University of British Columbia. His research uses genomics and bioinformatics to understand lethal prostate and bladder cancer and identify potential new targets for therapy. In this latest instalment of our series highlighting early-career researchers in biology, Dr. Wyatt tells us about research interests and career and about the challenges of the demanding research faculty workload. We're sure many of our readers will appreciate Dr. Wyatt's advice on the importance of learning to say "no".
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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 | 0.035 | 0.058 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.033 | 0.018 |
| Scholarly communication | 0.011 | 0.015 |
| Open science | 0.004 | 0.009 |
| Research integrity | 0.014 | 0.057 |
| Insufficient payload (model declined to judge) | 0.004 | 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".