Effect of SARS-CoV-2 infection on the liver
Bibliographic record
Abstract
There have been numerous concerns about the disease and how it affects the human body since the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic began in December 2019. The impact of SARS-CoV-2 on the liver is being carefully investigated due to an increase in individuals with hepatitis and other liver illnesses, such as alcoholic liver disease. Additionally, the liver is involved in the metabolism of numerous drugs used to treat comorbidities and coronavirus disease 2019 (COVID-19). Determining how SARS-CoV-2 affects the liver and what factors place individuals with COVID-19 at a higher risk of developing liver problems are the two main objectives of this study. This evaluation of the literature included research from three major scientific databases. To provide an update on the current impact of COVID-19 on the liver, data was collected and relevant information was incorporated into the review. With more knowledge about the effect of the disease on the liver, better management and therapeutics can be developed, and education can ultimately save lives and reduce the long-term impact of the pandemic on our population.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.033 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".