Role of Translesion Synthesis DNA Polymerases in DNA Replication in the Presence of a Weak DNA Polymerase δ in <i>Saccharomyces cerevisiae</i>
Bibliographic record
Abstract
This retraction has been requested by the corresponding author Likui Zhang, citing authorship concerns detailed below. The article (10.1534/g3.117.300097) was submitted and approved for publication without proper acknowledgement of funding, experiment design, data interpretation, and manuscript contributions contributed by Dr. Linda Reha-Krantz of the University of Alberta, Canada and additional research personnel and several students. All work by Dr. Zhang was done under the supervision of Dr. Reha-Krantz in Reha-Krantz’s lab, the experiments designed by Reha-Krantz, and the research funded by Reha-Krantz’s grants. Dr. Zhang was involved with the research as a Postdoctoral Scholar in Dr. Reha-Krantz’s lab and shared in the research with Alina Radziwon and RanRan Zhang who constructed the mutant strains. Dr. Linda Reha-Krantz has declined to be listed as an author due to various concerns, which had been shared with Dr. Zhang. Additionally, the authors listed on the early online version of the paper do not meet authorship criteria for G3: Genes|Genomes|Genetics, which was discovered by G3 post-publication after Dr. Zhang’s requested removal of the authors. Both Dr. Zhang and G3 apologize to our readers for any inconvenience caused by this retraction.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.003 |
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".