International Society for Stem Cell Research 2011, ninth annual meeting in Toronto (June 15–June 18, 2011)
Bibliographic record
Abstract
The International Society for Stem Cell Research ninth annual meeting in 2011 was held in Toronto, Canada.The meeting began within an earnest welcome by the president, Elaine Fuchs.The initial session was named "Past, Present, and Future" to showcase a historical perspective of stem cell research, and then presented information on how to implement stem cell based therapeutic strategies in humans.The marketing of stem cell therapies before their safety and efficacy have been demonstrated is an ongoing issue.Irving Weissman (Stanford University School of Medicine, USA) emphasized the importance of clear nomenclature in establishing the definition of any particular adult stem cell line.Single-cell clonality in conjunction with transplantation, as employed in the hematopoietic stem cell (HSC) field, he argued, is absolutely required for a rigorous definition of stem cells.He laid out a set of criteria that should be in place before marketing proceeds: (1) preclinical proof of principle; (2) verification of data in independent laboratories; (3) review by involvement of a medical ethics committee to protect the rights of human donors and their samples; and (4) approval by an official regulatory body such as the U.S. Food and Drug Administration (FDA).
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.129 | 0.071 |
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".