Early-career researchers: an interview with Heath MacMillan
Bibliographic record
Abstract
Heath MacMillan is an Assistant Professor at Carleton University, Canada, where he studies the physiological mechanisms limiting ectotherm performance. He received his Bachelor's degree in biology from the University of Western Ontario, Canada, in 2008 before completing his PhD in 2013 with Brent Sinclair and Jim Staples at the same institution. After undertaking a postdoc with Johannes Overgaard at Aarhus University, Denmark, MacMillan was awarded a Banting Fellowship, which he took in the laboratory of Andrew Donini at York University, Canada.
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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 | 0.022 | 0.042 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.028 | 0.016 |
| Scholarly communication | 0.011 | 0.016 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.011 | 0.033 |
| Insufficient payload (model declined to judge) | 0.008 | 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".