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Record W2339231138 · doi:10.24095/hpcdp.34.2/3.13

Report Summary - Seniors' Falls in Canada: Second Report: key highlights

2014· article· en· W2339231138 on OpenAlexaffvenueabout
Arne Stinchcombe, Natasha Kuran, Susan Powell

Bibliographic record

VenueChronic diseases and injuries in Canada · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicHealth disparities and outcomes
Canadian institutionsPublic Health Agency of Canada
Fundersnot available
KeywordsHarmPublic healthMedicineGerontologyOccupational safety and healthSuicide preventionCause of deathInjury preventionPoison controlMedical emergencyPsychologyNursingDisease

Abstract

fetched live from OpenAlex

Injury in Canada is a serious public health concern. Injuries are a leading cause of hospitalization for children, young adults and seniors and a major cause of disability and death. Falls remain the leading cause of injury-related hospitalizations among Canadian seniors, and data from the Canadian Community Health Survey - Healthy Aging indicate that 20% of seniors living in the community reported a fall in the previous year, with a higher prevalence among older seniors, i.e., those aged over 80 years. Falls and associated outcomes not only harm the injured individuals but also affect their families, friends and care providers; they also place considerable pressure on the health care system. However, we do know that these personal and economic costs can be avoided through injury prevention activities. The Seniors' Falls in Canada: Second Report provides policy makers, researchers, community programmers and practitioners with current data and trends on falls, injuries and hospitalizations among Canadian adults aged 65 years and over. This report is intended for use in public health research, policy development and practice.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.488
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.006
GPT teacher head0.254
Teacher spread0.248 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations66
Published2014
Admission routes3
Has abstractyes

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