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Record W2079465529 · doi:10.1093/alcalc/agu021

Alcoholic Liver Disease: A Synopsis of the Charles Lieber's Memorial Symposia 2009-2012

2014· article· en· W2079465529 on OpenAlexaff
Manuela G. Neuman, Lawrence Cohen, S. Zakhari, Radu M. Nanau, Sebastian Mueller, Marguerite Schneider, Charles Parry, Rachele Isip, Helmut K. Seitz

Bibliographic record

VenueAlcohol and Alcoholism · 2014
Typearticle
Languageen
FieldMedicine
TopicAlcohol Consumption and Health Effects
Canadian institutionsSunnybrook Health Science CentreHealth Sciences CentreUniversity of Toronto
Fundersnot available
KeywordsMedicinePhysiologyGerontology

Abstract

fetched live from OpenAlex

This paper is based upon the 'Charles Lieber Satellite Symposia' organized by Manuela G. Neuman at each of the 2009-2012 Research Society on Alcoholism (RSA) Annual Meetings. The presentations represent a broad spectrum dealing with alcoholic liver disease (ALD). In addition, a literature search (2008-2013) in the discussed area was performed in order to obtain updated data. The presentations are focused on genetic polymorphisms of ethanol metabolizing enzymes and the role of cytochrome P4502E1 (CYP2E1) in ALD. In addition, alcohol-mediated hepatocarcinogenesis, immune response to alcohol and fibrogenesis in alcoholic hepatitis as well as its co-morbidities with chronic viral hepatitis infections in the presence or absence of human deficiency virus are discussed. Finally, emphasis was led on alcohol and drug interactions as well as liver transplantation for end-stage ALD.

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)0.002
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: Not applicable
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.013
Threshold uncertainty score0.044

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0020.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0060.005
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0010.002
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0130.005

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 head0.043
GPT teacher head0.311
Teacher spread0.268 · 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
GenreReview

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

Citations10
Published2014
Admission routes1
Has abstractyes

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