IAGG NORTH AMERICAN REGION: FALLS PREVENTION—NEW INITIATIVES FROM THE CANADIAN GERIATRICS SOCIETY FALLS SPECIAL INTEREST GROUP
Bibliographic record
Abstract
Falls are a quintessential geriatric syndrome. Its study and the approaches developed for their prevention contributed to the establishment of geriatric medicine as a distinct field of specialty practice. Despite the myriad of studies aimed at improving our understanding of their pathophysiology and the clinical trials designed to establish effective strategies to prevent falls and fall-related injuries, there are still important gaps in what we know about this challenging and complex syndrome. This symposium will outline some of the work on fall prevention being done by members of the Falls Prevention Group, a national initiative designed to address knowledge gaps in falls prevention started by the Canadian Geriatrics Society. The Falls Prevention Clinics (University of British Columbia) have developed a physiological approach to falls prevention focusing on an innovative use of the Physiological Fall Profile and new methods of addressing syncopal etiologies of falls such as orthostatic hypotension and postprandial hypotension. The Gait and Brain Laboratory (University of Western Ontario) focuses on the complex interplay between gait, cognition and fall risk. This group will discuss how gait assessment provides a window into future interventions to prevent falls in cognitively impaired patients, a group of patients that have been notoriously resistant to standard preventative interventions. The Calgary Falls Prevention Clinic (Alberta Health Services – Calgary Zone) has developed a standardized approach to preventing falls in older adults. The success and challenges of implementing this protocol for community-dwelling older adults and integrating its activities within the health care system will be presented.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.007 | 0.002 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.018 | 0.005 |
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".