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World guidelines for falls prevention and management for older adults: a global initiative
Manuel Montero‐Odasso, Nathalie van der Velde, Finbarr C. Martin, Mirko Petrović, Maw Pin Tan, Jesper Ryg, Sara G. Aguilar-Navarro, Neil B. Alexander, Clemens Becker, Hubert Blain, Robbie Bourke, Ian D. Cameron, Richard Camicioli, Lindy Clemson, Jacqueline Close, Kim Delbaere, Leilei Duan, Gustavo Duque, Suzanne M Dyer, Ellen Freiberger, David A. Ganz, Fernando Gómez, Jeffrey M. Hausdorff, David B. Hogan, Susan M. Hunter, José Ricardo Jáuregui, Nellie Kamkar, Rose Anne Kenny, Sarah E Lamb, Nancy K. Latham, Lewis A. Lipsitz, Teresa Liu‐Ambrose, Pip Logan, Stephen R. Lord, Louise Mallet, David Marsh, Koen Milisen, Rogelio Moctezuma‐Gallegos, Meg E. Morris, Alice Nieuwboer, Mônica Rodrigues Perracini, Frederico Pieruccini‐Faria, Alison Pighills, Catherine M. Said, Ervin Sejdić, Catherine Sherrington, Dawn A. Skelton, Sabestina Dsouza, Mark Speechley, Susan Stark, Chris Todd, Bruce R. Troen, Tischa van der Cammen, Joe Verghese, Ellen Vlaeyen, Jennifer Watt, Tahir Masud, Devinder Kaur Ajit Singh, Edgar Aguilera Caona, Natalie E. Allen, Cedric Anweiller, Alberto Avila-Funes, Renato Barbosa dos Santos, Frances Batchelor, Marla Beauchamp, Canan Birimoglu, Kayla Bohlke, Robert Bourke, Christina Alonzo Bouzòn, Stephanie A. Bridenbaugh, Patricio Gabriel Buendia, Colleen G. Canning, Carlos Cano, Juan Carlos Carbajal, Daniela Cristina Carvalho de Abreu, Álvaro Casas‐Herrero, Alejandro Ceriani, Matteo Cesari, Lorenzo Chiari, Luis Manuel Cornejo Alemán, Rik Dawson, Paul Doody, Toby J. Ellmers, Nicola Fairhall, Luigi Ferrucci, James Frith, Homero Gac Espinola, Fabiana Giber, José Fernándo Gómez, Luis Miguel Gutiérrez‐Robledo, Sirpa Hartikainen, Chek Hooi Wong, Simon Howe, Javier Perez Jara, Ricardo Jauregui, A. Jellema, Suen Jenni, D. Jepson, Sebastiana Kalula, Ngaire Kerse, Olive Kobusingye, Reto W. Kressig, Wing S Kwok, Mei Ling Lim, Roberto Alves Lourenço, Kenneth Madden, Pedro Marín-Larraín, Diego Martínez Padilla, Sumaiyah Mat, Lisa McGarrigle, Bill McIlroy, Felipe Melgar-Cuellar, Jasmine C. Menant, Alberto Mimenza, Irfan Muneeb, Hossein Negahban, Mireille Norris, Giulia Ogliari, Juliana Oliveira, José F. Parodi, Sergio Pérez, José Ernesto Picado Ovares, Marina B. Pinheiro, Eveline P. van Poelgeest, Xinia Ramirez Ulate, Katie Robinson, Ryota Sakurai, Marcelo Schapira, Lotta J Seppala, Aldo Sgaravatti, Yu Song, Munira Sultana, Anisha Suri, Morag E. Taylor, Katja Thomsen, Anne Tiedemann, Susana Lucia Tito, Chang Won Won, G. A. Rixt Zijlstra
Bibliographic record
VenueAge and Ageing · 2022
Typearticle
Languageen
FieldHealth Professions
TopicBalance, Gait, and Falls Prevention
Canadian institutionsSt. Michael's HospitalUniversité de MontréalUniversity of British ColumbiaVancouver Coastal Health Research InstituteVancouver Coastal HealthMcGill University Health CentreMcGill UniversityUniversity of CalgaryWomen and Children’s Health Research InstituteUniversity of AlbertaParkwood InstituteLawson Health Research InstituteUniversity of TorontoWestern University
FundersNational Institute on AgingCanadian Institutes of Health ResearchNational Institute for Health and Care Research
KeywordsMedicineFall preventionFalls in older adultsGerontologyInjury preventionPoison controlMedical emergency
Abstract
OpenAlex records an abstract for this work, but it could not be fetched just now.
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.
metaresearch head score (Codex)0.039
metaresearch head score (Gemma)0.054
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.039
Threshold uncertainty score0.208
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.039 | 0.054 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.006 |
| Bibliometrics | 0.012 | 0.008 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.009 | 0.007 |
| Research integrity | 0.011 | 0.009 |
| Insufficient payload (model declined to judge) | 0.009 | 0.011 |
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 head0.065
GPT teacher head0.406
Teacher spread0.341 · how far apart the two teachers sit on this one work
Validation status
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.
The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreMethods
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
Citations1,510
Published2022
Admission routes2
Has abstractyes