Bibliographic record
Abstract
Falls are the most common injury in older adults. more than one-third of seniors fall each year and half of them suffer repeated falls. In an institutional setting, almost half of seniors will have a fall each year. Compared to a younger population, seniors have 9 times more fall injuries, and up to 25% of seniors who fall experience a serious injury. The most serious injury is a hip fracture, which often leads to institutionalization and pain, loss of mobility and independence. Of all hip fractures in older adults, >90% are due to a fall. The consequences of falls are expected to increase as the population ages. It is predicted that by 2030 the number of injuries caused by falls will be 100% higher than current rates. In addition to direct physical injury to the person, falls also cause indirect harm, such as the development of fear of falling, resulting in a lack of confidence and eventual deconditioning. The health care system is also affected by increased hospital admissions, emergency department visits and ongoing rehabilitation. Health care professionals, the public and the media may interpret the term “fall” differently. The currently accepted definition for a fall is: a sudden, unintentional change in position causing an individual to land at a lower level, on an object, the floor or the ground (other than as a consequence of sudden onset of paralysis, epileptic seizure or overwhelming external force). Because of their multifactorial causes and the medical complexity of older adults, falls are a challenge for health care professionals to address. Fortunately, there is evidence regarding risks and effective interventions that can reduce falls.
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 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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.003 |
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".