BEST PRACTICES OF FOUR GLOBAL INNOVATION CENTERS TO IMPROVE THE LIVES OF OLDER ADULTS
Bibliographic record
Abstract
This symposium brings together innovation centers from Canada, Ireland, the US and China who will share best practices for improving the lives of older adults by advancing the development and translation of technology in both clinical and community based settings. The Schlegel-UW Research Institute for Aging, Waterloo, Canada has developed a Centre for learning, research and innovation in long-term care through research-informed practice change and innovation in workforce preparedness. Their campus includes a long term care center, a workforce teaching and research facility that houses living classrooms and research labs. The Ireland Smart Ageing Exchange (ISAX), Ireland has established an independent network of businesses, academic institutions, government agencies and NGOs collaborating to fast-track research, development and commercialization of solutions for the global smart ageing economy. The Thrive Center, Louisville, Kentucky is an innovation center that partners closely with the Institute for Sustainable Health & Optimal Aging, University of Louisville to promote life-long wellness in order to transform the quality of life and care for the global aging population. It acts as a hub for older adults, academia and industry to experience and create innovative products, services and education that will promote sustainable health and optimal aging. The Genesis Innovation Center housed within the Qinhuangdao Taisheng GRS International Rehabilitation Center is a state-of-the-art facility designed to bring the best care to the people of China. Genesis has been designed for guests to interact with some of the newest technologies created to improve healthy living and maximize independence.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".