Proceedings: Regenerative Medicine for Lung Diseases: A CIRM Workshop Report
Bibliographic record
Abstract
The mission of the California Institute of Regenerative Medicine (CIRM) is to accelerate treatments to patients with unmet medical needs. In September 2016, CIRM sponsored a workshop held at the University of California, Los Angeles, to discuss regenerative medicine approaches for treatment of lung diseases and to identify the challenges remaining for advancing such treatments to the clinic and market approval. Workshop participants discussed current preclinical and clinical approaches to regenerative medicine in the lung, as well as the biology of lung stem cells and the role of stem cells in the etiology of various lung diseases. The outcome of this effort was the recognition that whereas transient cell delivery approaches are leading the way in the clinic, recent advances in the understanding of lung stem cell biology, in vitro and in vivo disease modeling, gene editing and replacement methods, and cell engraftment approaches raise the prospect of developing cures for some lung diseases in the foreseeable future. In addition, advances in in vitro modeling using lung organoids and "lung on a chip" technology are setting the stage for high quality small molecule drug screening to develop treatments for lung diseases with complex biology. Stem Cells Translational Medicine 2017;6:1823-1828.
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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 | 0.007 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.006 | 0.008 |
| Insufficient payload (model declined to judge) | 0.039 | 0.018 |
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".