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Record W4200383077 · doi:10.29169/1927-5951.2021.11.18

Anthropometry and Liver Function Parameters in Individuals with Metabolic Syndrome

2021· article· en· W4200383077 on OpenAlexvenueno aff
Adebowale Emmanuel Aladejana, Elizabeth Bosede Aladejana

Bibliographic record

VenueJournal of Pharmacy and Nutrition Sciences · 2021
Typearticle
Languageen
FieldMedicine
TopicLiver Disease Diagnosis and Treatment
Canadian institutionsnot available
Fundersnot available
KeywordsMetabolic syndromeFatty liverPhlebotomyMedicineAnthropometryLiver function testsLiver functionInternal medicinePhysiologyObesityDisease

Abstract

fetched live from OpenAlex

Metabolic syndrome (MS) is a metabolic condition commonly associated with central adiposity and altered liver function parameters (LFPs). Several studies have suggested these altered LFPs as a result of fatty liver diseases (e.g., non-alcoholic fatty liver diseases) often prevalent in MS. Since altered LFPs are very common in MS, there is a possibility they can be used as predictors of MS. However, only a few studies have been carried out to evaluate this possibility. This study, therefore, aimed to evaluate the potential of LFPs as predictors or risk factors of MS. The study groups included 50 individuals diagnosed with MS (case group) and 50 apparently normal individuals (control) from Ibadan, Oyo State, Nigeria. Anthropometric measurements, phlebotomy, liver function tests, and lipid profile estimations were done using standard procedures. (The result and conclusion section has been omitted).

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 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)0.000
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 score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.041
GPT teacher head0.335
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 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

Citations0
Published2021
Admission routes1
Has abstractyes

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