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Record W6901521191 · doi:10.60692/d1ewc-yxq24

Updates on Traditional Medicinal Plants for Hepatocellular Carcinoma

2016· article· en· W6901521191 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

VenueGreater South Information System · 2016
Typearticle
Languageen
FieldMedicine
TopicAndrographolide Research and Applications
Canadian institutionsInstitute of Infection and Immunity
Fundersnot available
KeywordsAndrographis paniculataHepatocellular carcinomaMedicinal plantsPhytotherapyLiver cancerAloe veraCancer

Abstract

fetched live from OpenAlex

Aim: Hepatocellular carcinoma (HCC) is a major worldwide problem primarily caused by hepatitis B and C virus infection. End stage liver cancer treatment options are limited thus requiring expensive liver transplantation which is not available in many countries. Methods: Several herbal compounds and herbal composite formulas have been studied through in-vitro and in vivo as an anti-HCC agent, enhancing our knowledge about their biological functions and targets. In this article, arecent update on the herbal medicine has been provided with reference to liver cancer. Results: For the sake of clarity, the effective herbal compounds, clinical studies of herbal composite formula, cell culture, and animal model studies safety are discussed. The effects of many herbal active compounds of Annona atemoya, Andrographis paniculata, Boerhaviadiffusa, Piper longum, Podophyllum hexandrum, Phyllanthus amarus, and Terminalia chebula, and herbal composite formula on autophagy, apoptosis, antioxidant, and inflammation characteristicshave been provided. Conclusion: This will enhance our understanding on the prevention and treatment of HCC by herbal active compounds and herbal composite formulas.

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 score0.097
Threshold uncertainty score0.819

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)0.0000.001

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 head0.085
GPT teacher head0.254
Teacher spread0.169 · 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