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Dynapenia and Metabolic Health in Obese and Nonobese Adults Aged 70 Years and Older: The LIFE Study
Mylène Aubertin‐Leheudre, Stephen D. Anton, Todd M. Manini, Roger A. Fielding, Anne B. Newman, Tim Church, Stephen B. Kritchevsky, David E. Conroy, Mary Mcdermott, Anda Botoseneanu, Marco Pahor, Thomas M. Gill, Carlos A. Vaz Fragoso, Jack M. Guralnik, Christiaan Leeuwenburgh, Connie Caudle, Lauren Crump, Latonia Holmes, Jocelyn Lee, Ching-ju Lu, Michael E. Miller, Mark A. Espeland, Walter T. Ambrosius, William B. Applegate, Robert P. Byington, Delilah Cook, Curt D. Furberg, Lea N. Harvin, Leora Henkin, M. Hepler, Fang‐Chi Hsu, Laura Lovato, Wesley Roberson, Julia Rushing, Scott Rushing, Cynthia L. Stowe, Michael P. Walkup, Don Hire, W. Jack Rejeski, Jeffrey A. Katula, Peter H. Brubaker, Shannon L. Mihalko, Janine M. Jennings, Sergei Romashkan, Kushang V. Patel, Denise E. Bonds, Bonnie Spring, Diana Kerwin, Kathryn Domanchuk, Rex Graff, Alvito Rego, Timothy S. Church, Steven N. Blair, Valerie H. Myers, Ron Monce, Nathan E. Britt, Melissa Harris, Ami Parks McGucken, Ruben Rodarte, Heidi K. Millet, Catrine Tudor‐Locke, Ben P. Butitta, Sheletta G. Donatto, Shannon Cocreham, Abby C. King, Cynthia M. Castro, William L. Haskell, Randall S. Stafford, Leslie A. Pruitt, Kathy Berra, Veronica Yank, Miriam E. Nelson, Sara C. Folta, Edward M. Phillips, Christine K. Liu, Erica McDavitt, Kieran F. Reid, Dylan Kirn, Evan Pasha, Won S. Kim, Vince E. Beard, Eleni X. Tsiroyannis, Cynthia Hau, Susan Nayfield, Thomas W. Buford, Michael Marsiske, Bhanuprasad Sandesara, Jeffrey D. Knaggs, Megan S. Lorow, William C. Marena, Irina Korytov, Holly Morris, Margo Fitch, Floris Singletary, Jackie Causer, Katie A. Radcliff, Stephanie A. Studenski, Bret H. Goodpaster, Nancy W. Glynn, Oscar Lopez, Neelesh K. Nadkarni, Kathy Williams, Mark A. Newman, George Grove, Janet T. Bonk, Jennifer Rush, Piera Kost, Diane G. Ives, Anthony P. Marsh, Tina E. Brinkley, Jamehl Demons, Kaycee M. Sink, Kimberly Kennedy, Rachel Shertzer‐Skinner, Abbie Wrights, Rose Fries, Deborah Barr, Robert S. Axtell, Susan S. Kashaf, Nathalie de Rekeneire, Joanne M. McGloin, Karen C. Wu, Denise Shepard, Barbara Fennelly, Lynne Iannone, Raeleen Mautner, Theresa Sweeney Barnett, Sean N. Halpin, Matthew Brennan, Julie A. Bugaj, Maria Zenoni, Bridget M Mignosa, Jeff D. Williamson, Hugh C. Hendrie, Stephen R. Rapp, Joe Verghese, Nancy Woolard, Janine Jennings, Valerie K. Wilson, Carl J. Pepine, Mario Ariet, Eileen Handberg, Daniel Deluca, James O. Hill, Anita Szady, Geoffrey Chupp, Gail M. Flynn, John Hankinson, Erik J. Groessl, Robert M. Kaplan
Bibliographic record
VenueJournal of the American Medical Directors Association · 2016
Typearticle
Languageen
FieldMedicine
TopicNutrition and Health in Aging
Canadian institutionsUniversité du Québec à Montréal
FundersDuke Claude D. Pepper Older Americans Independence Center, Duke Aging Center, Duke UniversityEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentNational Center for Research ResourcesNational Heart, Lung, and Blood InstituteNational Institute on AgingTufts UniversityFonds de Recherche du Québec - SantéNational Institutes of HealthUniversity of FloridaUniversity of PittsburghWake Forest UniversityStanford UniversityU.S. Department of Veterans AffairsYale UniversityU.S. Department of Agriculture
KeywordsMedicineAbdominal obesityWaistOdds ratioObesityMetabolic syndromeBody mass indexBlood pressureConfidence intervalInternal medicine
Abstract
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 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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.024
Threshold uncertainty score0.047
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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 head0.009
GPT teacher head0.316
Teacher spread0.306 · 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 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
Citations35
Published2016
Admission routes2
Has abstractno