Corrigendum to “Mechanism of chromium-induced toxicity in lungs, liver, and kidney and their ameliorative agents” [Biomed. Pharmacother. 151, July 2022, 113119]
Bibliographic record
Abstract
This corrigendum has been retracted: Please see Elsevier Policy on Article Correction, Retraction and Removal ( https://www.elsevier.com/about/policies/article-withdrawal ). This corrigendum has been retracted at the request of the editor. A corrigendum for the article Mechanism of Chromium - induced Toxicity in Lungs, Liver and Kidney and their ameliorative agents Biomed. Pharmacother. 151 (2022) 113119. https://doi.org/10.1016/j.biopha.2022.113119 was originally published in Dec 2024. However, an investigation conducted on behalf of the journal by Elsevier's Research Integrity & Publishing Ethics team has identified further citation errors in the original article to which the corrigendum referred. Given the nature and extent of the citation errors, the editor has lost confidence in the integrity of the article and has determined to retract both the original article and this corrigendum related to it.
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 | 0.002 | 0.013 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.009 | 0.006 |
| Insufficient payload (model declined to judge) | 0.159 | 0.121 |
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".