International Coordination of Large-Scale Human Induced Pluripotent Stem Cell Initiatives: Wellcome Trust and ISSCR Workshops White Paper
Bibliographic record
Abstract
There is growing recognition of the potential value of human induced pluripotent stem cells (hiPSC) for understanding disease and identifying drugs targets. This has been reflected in the establishment of multiple large-scale hiPSC initiatives worldwide. Representatives of these met recently at a workshop supported by the Welcome Trust in the UK and in a focus session at the 2014 ISSCR annual meeting in Vancouver. The purpose was to discuss strategies for making thousands of hiPSC lines widely available with as few restrictions as possible while retaining financial viability and donor privacy. The outcome of these discussions is described here.
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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 | 0.100 | 0.040 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.014 | 0.006 |
| Open science | 0.009 | 0.029 |
| Research integrity | 0.015 | 0.013 |
| Insufficient payload (model declined to judge) | 0.104 | 0.039 |
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".