David Herman Maclennan - Bibliography from DAVID HERMAN MACLENNAN 3 July 1937 — 24 June 2020 Elected FRS 1994
Bibliographic record
Abstract
David Herman MacLennan, one of Canada's foremost biomedical scientists, was known internationally for his research on the molecular mechanism of muscle contraction in human health and disease. David was born on 3 July 1937 in Swan River, Manitoba, and grew up in farm country. After obtaining a BS (Agriculture) in plant science from the University of Manitoba in 1959, David completed his MSc (1961) and PhD (1963) in biology at Purdue. A post-doctoral fellowship at the Enzyme Institute at the University of Wisconsin followed, where he was appointed as an assistant professor (1964–1968). At Wisconsin David published a series of elegant papers on the isolation and characterization of the mitochondrial ATPase and protein components of the electron transfer system. In 1969 he was recruited back to Canada as an associate professor in the Banting and Best Department of Medical Research at the University of Toronto, where he spent the rest of his illustrious career. Here, David shifted his focus to determine how calcium regulates muscle contraction with a focus on the role of the sarcoplasmic reticulum (SR). David was a scientist who knew where a field was going and he often got there first, incorporating new technologies along the way. His early discovery of the Ca<sup>2+</sup> ATPase pump that controls calcium uptake into the SR was the key to muscle relaxation. His lab systematically characterized the components of the SR, including the ryanodine receptor that acts as a calcium release channel to allow muscle contraction. David's discoveries of these molecular mechanisms and their application to debilitating muscle disease is an inspiring scientific legacy. Although David published hundreds of papers, many cited hundreds of times, gave hundreds of invited seminars and won many prestigious awards, including Fellow of the Royal Society of London in 1994, his greatest legacy is the people he trained, many of whom went on to leadership positions in research and at universities around the world.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.195 | 0.007 |
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; both teacher heads agree on what is shown here.
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".