Bibliographic record
Abstract
In 2001, the Stem Cell Network was the first of its kind, a bold initiative to forge and nurture pan-Canadian collaborations involving researchers, engineers, clinicians and private and public sector partners. Canada's broad and deep pool of stem cell talent proved to be a fertile ground for such an initiative, giving rise to a strong, thriving network that, 7 years later, can list innovative cell expansion and screening technologies, early-phase clinical trials for stroke, pulmonary hypertension, muscular dystrophy and cornea replacement, and leading discourse on ethical, legal and social issues among its accomplishments. As it moves into its second and final phase of funding, the Stem Cell Network continues to push boundaries and has set its sights on overcoming the obstacles that impede the transfer of research findings to clinical applications, commercial products and public policy.
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 | 0.084 | 0.063 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.006 | 0.028 |
| Scholarly communication | 0.014 | 0.009 |
| Open science | 0.003 | 0.021 |
| Research integrity | 0.016 | 0.028 |
| Insufficient payload (model declined to judge) | 0.009 | 0.004 |
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".