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Record W3006044359

The My Active and Healthy Aging (My-AHA) ICT platform to detect and prevent frailty in older adults: Randomized control trial design and protocol

2018· article· en· W3006044359 on OpenAlexaff
Mathew J. Summers, Innocenzo Rainero, Alessandro Vercelli, Georg Aumayr, Helios De Rosario, Michaela Mönter, Chiara Carbone, Elisa Rubino, Ivone de Melo Sousa, Maria João M. Vasconcelos, Pedro Madureira, Jaime Ribeiro, Neide Pereira Cardoso, Eleftheria Giannouli, Wierd P Zijlstra, Sebastian Schnieder, S.D. Roelen, L. Kächele, Jarek Krajewski, J. Laparra, Jaume Serrano, Ernie Medina, Úrsula Martínez, Marco Bazzani, C. Cogerino, Gregory Toso, G. Tommasone, D. Bleier, Noemi Sturm, Niina E. Kaartinen, Andrew Kern, Stephan Bandelow, Nils Georg Niederstrasser, Daryoush Daniel Vaziri, Andrew Tabatabaei, Philip Gouverneur, P. Lagodzinski, M. Grzegorek, H. Shariat Yazdi, Kunji Shirahama, Wulf, Dalila Burin, Ludovico Ciferri

Bibliographic record

VenueUSC Research Bank (University of the Sunshine Coast) · 2018
Typearticle
Languageen
FieldMedicine
TopicFrailty in Older Adults
Canadian institutionsInstitute of Aging
Fundersnot available
KeywordsMedicinePsychosocialRandomized controlled trialPsychological interventionGerontologyPopulationPhysical therapyEnvironmental healthPsychiatrySurgery
DOInot available

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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)0.007
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.032
Threshold uncertainty score0.107

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.009
Meta-epidemiology (narrow)0.0050.002
Meta-epidemiology (broad)0.0070.004
Bibliometrics0.0020.001
Science and technology studies0.0020.002
Scholarly communication0.0020.002
Open science0.0020.001
Research integrity0.0050.004
Insufficient payload (model declined to judge)0.0320.004

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 head0.050
GPT teacher head0.348
Teacher spread0.298 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designRandomized trial
Domainnot available
GenreProtocol

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

Citations0
Published2018
Admission routes1
Has abstractno

Explore more

Same venueUSC Research Bank (University of the Sunshine Coast)Same topicFrailty in Older AdultsFrench-language works237,207