A tribute to Alexander Davidson Bain: An NMR pioneer and mentor at McMaster University
Bibliographic record
Abstract
Abstract In this tribute to our friend, mentor and colleague Alexander Davidson Bain we have collectively recapitulated the milestones of his career at McMaster university. We start from Alex's scientific and educational achievements and continue with his accomplishments as a community and infrastructure builder. We attempt to provide a sense of the breadth and depth of his seemingly endless scientific contributions while at McMaster by briefly summarizing selected representative examples from his body of work. Following Alex's lead, the scientific account is mixed with anecdotes and “bits of wisdom” we fondly remember from our interactions and collaborations with him. We also touch upon his brilliant and nurturing educational style and his “aggregator” role within the McMaster and wider NMR communities. We conclude with a more personal picture of Alex D. Bain, in which his scientific excellence and profound intellect are inextricably tied to his kind, nurturing and optimistic character and to his uniquely wry humor. He was not just a “good guy,” he was the epitome of the “good guy.”
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.009 | 0.006 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.003 | 0.010 |
| Insufficient payload (model declined to judge) | 0.024 | 0.013 |
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".