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Record W2480881576 · doi:10.1155/2016/3056438

New Exploration of Chinese Herbal Medicines in Hepatology

2016· article· en· W2480881576 on OpenAlexaff
Yibin Feng, Man‐Fung Yuen, Qihe Xu, Xiao‐Yan Wen, David Q.‐H. Wang

Bibliographic record

VenueEvidence-based Complementary and Alternative Medicine · 2016
Typearticle
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicDrug-Induced Hepatotoxicity and Protection
Canadian institutionsUniversity of TorontoSt. Michael's Hospital
FundersMedical Research CouncilKidney Research UK
KeywordsHepatologyTraditional medicineMedicineInternal medicineAlternative medicineFamily medicinePathology

Abstract

fetched live from OpenAlex

Chronic liver diseases (CLD) are serious health-threatening problems worldwide. In particular, it is a significant healthcare burden in Southeast Asian countries where viral hepatitis is common. Regardless how the diseases are initiated, without proper intervention, CLD may gradually progress towards end-stage liver disease (ESLD), for which liver transplantation remains the only solution. Although this progression may be slow and gradual, there is no evidence showing that it could be reversed when cirrhosis has developed. Preventive intervention that may impede the progression of CLD is clinically favourable. Management of CLD depends on the etiology, and supporting treatment and hepatoprotective medicines are often provided. However, drug resistance and various adverse effects can lead to failure of treatment.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.431
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.306
GPT teacher head0.479
Teacher spread0.173 · 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.

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

Citations1
Published2016
Admission routes1
Has abstractyes

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