The DISCUSS Project: Induced Pluripotent Stem Cell Lines From Previously Collected Research Biospecimens and Informed Consent: Points to Consider
Bibliographic record
Abstract
Human somatic cell reprogramming is a leading technology for accelerating disease modeling and drug discovery. Research organizations are sponsoring initiatives to create libraries of induced pluripotent stem cell (iPSC) lines for broad distribution and application. Donor informed consent plays a critical role in supporting the ethical conduct of iPSC research. To date, our organizations have focused on informed consent considerations for somatic cell collection intended specifically for iPSC derivation and distribution. This article considers how somatic cells obtained under general (biomedical) research protocols can be used for iPSC derivation. We present draft Points to Consider regarding the use of human somatic cells for iPSC research. Our goal is to initiate a process designed to develop consensus for the use of previously collected specimens for iPSC research. We anticipate publishing final considerations in early 2014.
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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 | 0.183 | 0.239 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.012 |
| Scholarly communication | 0.010 | 0.010 |
| Open science | 0.004 | 0.009 |
| Research integrity | 0.039 | 0.020 |
| Insufficient payload (model declined to judge) | 0.010 | 0.008 |
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".