RETRACTION: Challenges of combined everolimus/endocrine therapy in hormone receptor-positive metastatic breast cancer
Bibliographic record
Abstract
To our readers:With deep regrets, we inform our Readers that the article Challenges of combined everolimus/endocrine therapy in hormone receptor-positive metastatic breast cancer (DOI: http://dx.doi.org/10.4081/oncol.2014.236), which has been published Ahead of Print in the first issue of Oncology Reviews (2014), contains verbatim text plagiarized from another paper.1The manuscript must be considered as retracted. On behalf of the Editorial Board of Oncology Reviews, I apologize to the Author of the manuscript whose text was plagiarized by Y. Abubakr and Y. Albushra that this was not picked up in the peer review process. I also apologize to the affected journal for the violation of copyright due to plagiarism. Oncology Reviews is uncompromising in its commitment to scientific integrity. When credible evidence of misconduct is brought to our attention, our commitment to the scientific record and to our readership requires immediate notification. Oncology Reviews is increasingly employing sophisticated software to detect plagiarism. Other journals use similar tools. Authors should be aware that most journals routinely employ plagiarism detection software, and that any plagiarism is likely to be detected.Camillo Porta, Editor-in-Chief Oncology Reviews Reference 1. André F. Enhancing effectiveness of endocrine therapy in hormone receptor-positive advanced breast cancer. Medscape Education Oncology. CME Released: 05/24/2013; Valid for credit through 05/24/2014. http://www.medscape.org/viewarticle/804496
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
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Other About the Canadian research system: no · About a Canadian topic: no | Not applicable | low |
| gpt | Research integrity Domain: not available · Genre: Other About the Canadian research system: no · About a Canadian topic: no | Not applicable | high |
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 | 0.008 | 0.113 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.014 | 0.021 |
| Insufficient payload (model declined to judge) | 0.010 | 0.009 |
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, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".