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Record W4210928714 · doi:10.1007/s40520-022-02080-5

Attributes and definitions of locomotor capacity in older people: a World Health Organisation (WHO) locomotor capacity working group meeting report

2022· letter· en· W4210928714 on OpenAlexfundno aff
Nicola Veronese, Germain Honvo, Jotheeswaran Amuthavalli Thiyagarajan, René Rizzoli, Cyrus Cooper, Olivier Bruyère, Christopher Mikton, Yuka Sumi, Theresa Diaz, Jean‐Yves Reginster, Anshu Banerjee, Al- Daghri Nasser, Sandrine Andrieu, Annweiler Cédric, Aubertin- Leheudre Mylène, Ivan Bautmans, Charlotte Beaudart, Becker Clemens, Bruyère Olivier, Fanny Buckinx, Campusano Claudia, Chandran Manju, Cherubini Antonio, C. Patrícia, Cruz- Jentoft Alfonso, Dennison Elaine, Fouasson Chailloux Alban, Fuggle Nick, Muthoni Gichu, Evelien Gielen, Guicheux Jérôme, Haugen Ida, Olivier Lamy, Francesco Landi, L. Pedersen Nancy, Lazaretti Castro Marise, Lewiecki Mike, Radmila Matijević, Mkinsi Ouafa, M.Mohammed Mubeen Ali, Njeze Ngozi, P Daniel, Reginster Jean-Yves, Rolland Yves, Saleh Yousef, Singer Andrea, Van der Velde Nathalie, Bruno Vellas, Visser Marjolein

Bibliographic record

VenueAging Clinical and Experimental Research · 2022
Typeletter
Languageen
FieldMedicine
TopicFrailty in Older Adults
Canadian institutionsnot available
FundersUniversite AngersUniversité de ToulouseNational Institute for Health and Care ResearchVrije Universiteit BrusselKing Saud UniversityMedical Research CouncilVersus ArthritisUniversität HeidelbergUniversité du Québec à MontréalSingapore General HospitalUniversità degli Studi di MilanoWorld Health OrganizationUniversité de LiègeUniversiteit Maastricht
KeywordsAction (physics)Variety (cybernetics)Older peopleGerontologyHealthy ageingAgeing societyActive ageingPsychologyHealth careMedicineNursingPolitical scienceAgeing

Abstract

fetched live from OpenAlex

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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)0.006
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.148
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.005
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 head0.291
GPT teacher head0.437
Teacher spread0.147 · 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.

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

Citations25
Published2022
Admission routes1
Has abstractyes

Explore more

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