Bibliographic record
Abstract
Abstract Ernest Armstrong McCulloch was half of the brilliant partnership that discovered haematopoietic stem cells (HSCs) and changed how we think about human tissue generation and regeneration. Based at the Ontario Cancer Institute (now the Princess Margaret Cancer Centre) in Toronto, the haematologist ‘Bun’ McCulloch, together with James E. Till, a physicist with a steel-trap mind, exercised their penchant for adventurous ‘big picture’ thinking in devising experiments to identify stem cells. This exceptional team was the first to demonstrate that HSCs have the dual capacity to self-renew and to differentiate into a vast array of mature haematopoietic cells. Their trainees, as well as investigators elsewhere, built on McCulloch and Till's findings not only to isolate and characterize HSCs and progenitors derived from them, but also to devise therapies for certain blood disorders. Later in his career, Ernest focused on characterizing the malignant cells of human leukaemias and determining the effects of various drugs on leukaemic cell growth. The implications of Till and McCulloch's work continue to be profound and underpin many significant breakthroughs in our knowledge of normal cellular physiology, pathophysiology, tumorigenesis and tissue transplantation. Indeed, regenerative medicine owes its very existence to the stem cell discoveries of McCulloch, Till and others. At times eccentric and demanding, but always well spoken, incisive and erudite, Ernest personified the outstanding research scientist cloaked in Canadian modesty. His legacy lives on in the bright therapeutic future emerging from the rigorous stem cell research being conducted in Canada and around the world.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.322 | 0.225 |
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".