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Record W4412902150 · doi:10.56367/oag-047-11859

Unravelling NASH and insulin resistance: Insights from the department of human health and nutritional sciences

2025· article· en· W4412902150 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueOpen Access Government · 2025
Typearticle
Languageen
FieldMedicine
TopicLiver Disease Diagnosis and Treatment
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsInsulin resistanceResistance (ecology)InsulinMedicineBiologyEndocrinology

Abstract

fetched live from OpenAlex

Unravelling NASH and insulin resistance: Insights from the department of human health and nutritional sciences Open Access Government sits down with a researcher from the Department of Human Health and Nutritional Sciences to discuss their groundbreaking work on nonalcoholic steatohepatitis (NASH) and insulin resistance. Their research delves into the molecular underpinnings of these increasingly prevalent conditions, offering new avenues for understanding, prevention, and treatment. NASH and insulin resistance are increasing public health problems with widespread social and economic consequences. Public health efforts must shift toward early detection, improved education, and targeted interventions that address the metabolic origins of the disease. By addressing obesity and promoting lifestyle changes, healthcare systems can help mitigate the growing impact of these interrelated chronic conditions.

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.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.108
Threshold uncertainty score0.247

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 head0.049
GPT teacher head0.382
Teacher spread0.332 · 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