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Record W2092170177 · doi:10.1016/j.jamda.2013.03.022

Frailty Consensus: A Call to Action

2013· article· en· W2092170177 on OpenAlexaff
John E. Morley, Bruno Vellas, Gabor Abellán van Kan, Stefan D. Anker, Roberto Bernabei, Matteo Cesari, Wm. Cameron Chumlea, Wolfram Doehner, Jonathan P Evans, Linda P. Fried, Jack M. Guralnik, Paul R. Katz, Theodore K. Malmstrom, Roger McCarter, Luis Miguel Gutiérrez‐Robledo, K. Rockwood, Stephan von Haehling, M. Vandewoude, Jeremy Walston

Bibliographic record

VenueJournal of the American Medical Directors Association · 2013
Typearticle
Languageen
FieldMedicine
TopicFrailty in Older Adults
Canadian institutionsDalhousie UniversityUniversity of Toronto
FundersEuropean Geriatric Medicine SocietyEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentSanofi
KeywordsMedicinePolypharmacyGerontologyVulnerability (computing)Weight lossGeriatricsDiseaseStressorMalnutritionPhysical therapyIntensive care medicinePsychiatryObesityInternal medicineComputer security

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)0.122
metaresearch head score (Gemma)0.191
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: Commentary · Consensus signal: Commentary
Teacher disagreement score0.182
Threshold uncertainty score0.643

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1220.191
Meta-epidemiology (narrow)0.0020.003
Meta-epidemiology (broad)0.0070.008
Bibliometrics0.0060.003
Science and technology studies0.0270.032
Scholarly communication0.0320.042
Open science0.0150.036
Research integrity0.1820.149
Insufficient payload (model declined to judge)0.0340.009

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 head0.019
GPT teacher head0.316
Teacher spread0.297 · 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 designNot applicable
Domainnot available
GenreCommentary

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

Citations4,091
Published2013
Admission routes1
Has abstractno

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