Stem Cells as an Emerging Paradigm in Stroke 3
Bibliographic record
Abstract
Cell-based therapy continues to grow as a new field to explore investigational treatments for stroke. Leaders from academia and industry convened an inaugural meeting in 2007 with members of the National Institutes of Health and Food and Drug Administration (FDA) to generate consensus-based guidelines on the development of cell therapies for stroke, entitled “Stem Cells as an Emerging Paradigm in Stroke” (STEPS).1 These guidelines focused on preclinical studies that are considered important as part of a development program to support clinical testing of cell therapies. The STEPS meeting also provided recommendations on the conduct of early-stage clinical trials. Given the rapid advances in the field, a second meeting was held in 2009 to update and expand these guidelines, which were published as STEPS 2.2 In December 2011, investigators in academia, industry leaders, and members of the National Institutes of Health and FDA gathered at a third meeting, STEPS 3, to discuss emerging data on the mechanisms of action of cell therapy, the barriers to successful translation from animal models to patients, and the design of current clinical trials for acute and chronic stroke. Since the prior STEPS meeting, there are now several active cell therapy platforms for stroke and other neurological disorders, in stages that range from preclinical to clinical trials, and with sponsors that include industry, the National Institutes of Health, and the California Institute of Regenerative Medicine. As the field continues to progress and as pilot clinical studies are starting to show safety for some cell types, it has become necessary to formulate a new set of guidelines that address topics not covered in prior STEPS publications. Specifically, the current document reflects a compilation of recommendations that focus on more advanced stages of clinical testing, as well as the testing of cell therapies in a broader …
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".