American Society for Bone and Mineral Research-Orthopaedic Research Society Joint Task Force Report on Cell-Based Therapies
Bibliographic record
Abstract
Cell-based therapies, defined here as the delivery of cells in vivo to treat disease, have recently gained increasing public attention as a potentially promising approach to restore structure and function to musculoskeletal tissues. Although cell-based therapy has the potential to improve the treatment of disorders of the musculoskeletal system, there is also the possibility of misuse and misrepresentation of the efficacy of such treatments. The medical literature contains anecdotal reports and research studies, along with web-based marketing and patient testimonials supporting cell-based therapy. Both the American Society for Bone and Mineral Research (ASBMR) and the Orthopaedic Research Society (ORS) are committed to ensuring that the potential of cell-based therapies is realized through rigorous, reproducible, and clinically meaningful scientific discovery. The two organizations convened a multidisciplinary and international Task Force composed of physicians, surgeons, and scientists who are recognized experts in the development and use of cell-based therapies. The Task Force was charged with defining the state-of-the art in cell-based therapies and identifying the gaps in knowledge and methodologies that should guide the research agenda. The efforts of this Task Force are designed to provide researchers and clinicians with a better understanding of the current state of the science and research needed to advance the study and use of cell-based therapies for skeletal tissues. The design and implementation of rigorous, thorough protocols will be critical to leveraging these innovative treatments and optimizing clinical and functional patient outcomes. In addition to providing specific recommendations and ethical considerations for preclinical and clinical investigations, this report concludes with an outline to address knowledge gaps in how to determine the cell autonomous and nonautonomous effects of a donor population used for bone regeneration. © 2019 American Society for Bone and Mineral Research.
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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 | 0.048 | 0.055 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.012 | 0.003 |
| Open science | 0.006 | 0.006 |
| Research integrity | 0.020 | 0.014 |
| Insufficient payload (model declined to judge) | 0.044 | 0.053 |
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".