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Record W4386021288 · doi:10.1055/a-2157-3318

COVID-19 and Liver Disease: An Evolving Landscape

2023· review· en· W4386021288 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

VenueSeminars in Liver Disease · 2023
Typereview
Languageen
FieldMedicine
TopicCOVID-19 Clinical Research Studies
Canadian institutionsSpinal Cord Injury BCUniversity of British Columbia
Fundersnot available
KeywordsMedicineLiver diseaseCoronavirus disease 2019 (COVID-19)DiseaseChronic liver diseasePandemicPopulationImmunologyViral hepatitisInternal medicineInfectious disease (medical specialty)Environmental healthCirrhosis

Abstract

fetched live from OpenAlex

The COVID-19 pandemic has resulted in significant worldwide morbidity and mortality. In this review, we examine the intricate relationships between COVID-19 and liver diseases. While respiratory manifestations of COVID-19 are well known, its impact and consequences in patients with liver diseases remain an area of ongoing investigation. COVID-19 can induce liver injury through various mechanisms and is associated with higher mortality in individuals with preexisting chronic liver disease. Mortality increases with the severity of chronic liver disease and the level of care required. The outcomes in patients with autoimmune hepatitis remain unclear, whereas liver transplant recipients are more likely to experience symptomatic COVID-19 but have comparable outcomes to the general population. Despite suboptimal immunological response, COVID-19 vaccinations are safe and effective in liver disease, although cases of autoimmune hepatitis-like syndrome have been reported. In conclusion, COVID-19 has significant implications in liver diseases; early recognition and treatments are important for improving patient 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.

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)0.084
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.905
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.084
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.112
GPT teacher head0.468
Teacher spread0.356 · 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