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Record W2895006340 · doi:10.1017/s0029665118001775

Sarcopenic obesity and insulin resistance: application of novel body composition models

2018· article· en· W2895006340 on OpenAlexaff
Iara Karise Santos Mendes, Eleonora Poggiogalle, B. Lee, Carla M. Prado, Gabriele Mocciaro, G. Mariniello, José Lara, Carla Lubrano, Andrea Lenzi, Lorenzo M. Donini, Mario Siervo

Bibliographic record

VenueProceedings of The Nutrition Society · 2018
Typearticle
Languageen
FieldMedicine
TopicNutrition and Health in Aging
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsComposition (language)Action (physics)Computer scienceContent (measure theory)Sarcopenic obesityInsulin resistanceSarcopeniaObesityMedicineEndocrinologyMathematicsLinguisticsPhysicsPhilosophy

Abstract

fetched live from OpenAlex

Sarcopenic Obesity (SO) is characterized by the co-occurrence of high adiposity (HA) and low muscle mass (LM) (1) and it has been linked to insulin resistance, inflammation and increased cardio-metabolic risk This cross-sectional study investigated the association between markers of insulin sensitivity and SO defined using three novel body composition definitions: 1) body composition phenotypes; 2) truncal fat mass/appendicular skeletal mass ratio (TrFM/ASM) load-capacity; 3) fat mass/fat free mass ratio (FM/FFM) load-capacity

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.074
Threshold uncertainty score0.295

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.032
GPT teacher head0.308
Teacher spread0.277 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations0
Published2018
Admission routes1
Has abstractyes

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