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Record W1607333160 · doi:10.1002/9781444346343.ch21

The Problem of Insulin Resistance and its Effect on Therapy

2011· other· en· W1607333160 on OpenAlexaff
Venessa Pattullo, Jacob George

Bibliographic record

Venuenot available
Typeother
Languageen
FieldMedicine
TopicHepatitis C virus research
Canadian institutionsToronto Western HospitalUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsInsulin resistanceHepatitis C virusChronic hepatitisMedicineInternal medicineInsulinInsulin sensitivityBody mass indexType 2 diabetesDiabetes mellitusHepatitis CAntiviral therapyGastroenterologyVirusEndocrinologyVirology

Abstract

fetched live from OpenAlex

Convincing epidemiologic data links chronic hepatitis C (CHC) to insulin resistance (IR), with a reported prevalence of 30–60%. IR in hepatitis C virus (HCV) infection is independent of body mass index (BMI) and is associated with higher serum HCV RNA levels. Consequently, a high prevalence of type 2 diabetes (T2DM) is observed in both cirrhotic and non-cirrhotic individuals with CHC. Consistent with these observations, improved insulin sensitivity is observed in those who achieve treatment-induced viral clearance, but not in those who fail to respond to therapy. Likewise, the greater the degree of IR, the lower the likelihood of treatment-induced viral clearance. This chapter will examine the relationship between CHC, IR, and treatment response, and the role of novel approaches to improve insulin sensitivity in order to enhance treatment outcomes.

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)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.007
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.002
Scholarly communication0.0020.002
Open science0.0000.001
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0070.002

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 head0.035
GPT teacher head0.324
Teacher spread0.289 · 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 designNot applicable
Domainnot available
GenreOther

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
Published2011
Admission routes1
Has abstractyes

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