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Record W2048798480 · doi:10.1016/j.jamda.2011.04.014

Sarcopenia With Limited Mobility: An International Consensus

2011· article· en· W2048798480 on OpenAlexaff
John E. Morley, Angela Marie Abbatecola, Josep M. Argilés, Vickie E. Baracos, Shalender Bhasin, Tommy Cederholm, Andrew J.S. Coats, Steven R. Cummings, William J. Evans, Kenneth C.H. Fearon, Luigi Ferrucci, Roger A. Fielding, Jack M. Guralnik, Tamara B. Harris, Akio Inui, Kamyar Kalantar‐Zadeh, Bridget‐Anne Kirwan, Giovanni Mantovani, Maurizio Muscaritoli, Anne B. Newman, Filippo Rossi Fanelli, Giuseppe Rosano, Ronenn Roubenoff, Morris Schambelan, Gerald H. Sokol, Thomas W. Storer, Bruno Vellas, Stephan von Haehling, Shing-Shing Yeh, Stefan D. Anker

Bibliographic record

VenueJournal of the American Medical Directors Association · 2011
Typearticle
Languageen
FieldMedicine
TopicNutrition and Health in Aging
Canadian institutionsUniversity of Alberta
FundersNational Institutes of Health
KeywordsSarcopeniaMedicineWastingCachexiaLean body massMuscle massPhysical medicine and rehabilitationPsychological interventionPhysical therapyInternal medicineBody weightCancer

Abstract

fetched live from OpenAlex

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 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)0.048
metaresearch head score (Gemma)0.050
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.048
Threshold uncertainty score0.252

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0480.050
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0040.005
Bibliometrics0.0060.006
Science and technology studies0.0020.002
Scholarly communication0.0060.006
Open science0.0090.006
Research integrity0.0150.015
Insufficient payload (model declined to judge)0.0060.003

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 head0.036
GPT teacher head0.331
Teacher spread0.294 · 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 designTheoretical or conceptual
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

Citations1,127
Published2011
Admission routes1
Has abstractyes

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