Bibliographic record
Abstract
Drug-induced liver injury (DILI) is a comprehensive phenomenon. The injury to the liver may occur as an unexpected and undesired reaction to a therapeutic dose of a drug (idiosyncratic reaction) or as an expected therapeutic effect of the direct (intrinsic) toxicity of a drug taken in a large enough dose to cause liver injury. The direct toxicity (type A) reactions represent an extension of the drug's therapeutic effect; they occur relatively frequently and are typically dose-related and frequency-of-exposure-related. By contrast, idiosyncratic reactions, or type B reactions, are unpredictable, occurring only in susceptible individuals, and are unrelated to the dose or frequency of exposure. DILI encompasses both acute and/or chronic hepatic lesions. The liver injury may be the only clinical manifestation of the adverse drug effect. Otherwise, it may be accompanied by injury to other organs, or by systemic manifestations. The liver injury may be observed in 1-8 days from taking the drug. DILI cases may result in the disapproval of a new drug or in the removal of a useful drug from the market by regulatory agencies. The purpose of this review is to provide guidance to facilitate the detection and assessment of hepatotoxicity induced by therapeutics that received market authorization. This review supports the safe and effective use of drugs by patients and guides laboratory medicine professional in determining the possible drug-induced liver damage.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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.
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 source (direct Gemma or distilled Codex), 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".