C.06 Retraction of scientific publications in neurosurgery
Bibliographic record
Abstract
Background: Despite increasing awareness of scientific fraud, no attempt has been made to assess its prevalence in neurosurgery. The aim of our review was to assess the chronological trend and reasons for the retraction of neurosurgical publications. Methods: We searched the EMBASE and MEDLINE databases using a comprehensive search strategy for retracted articles from January 1995 to December 2016. Archives of retracted articles on www.retractionwatch.com and the independent websites of neurosurgical journals were also searched. Data including the journal name and its impact factor, reason for retraction, country of origin, and citations were extracted. Results: A total of 72 studies were included for data extraction. Journal impact factor ranged from 0.24 to 14.4. Most studies(76%) were retracted within the last 5 years. The most common reason for retraction was because of a duplicated publication found elsewhere(25%), followed closely by plagiarism(21%), or falsifying data(17%). Other reasons included scientific errors/mistakes, author misattribution, and fraudulent peer review. Articles originated from several different countries and some were widely cited. Conclusions: Retractions of neurosurgical publications are increasing globally, mostly due to issues of academic integrity. Implementation of more transparent data sharing and screening as well as additional education for new researchers may help mitigate these issues moving forward.
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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 | MetaresearchResearch integrity Domain: Evaluation · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Systematic review | high |
| gpt | MetaresearchBibliometricsScholarly communicationResearch integrity Domain: Evaluation · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Systematic review | 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 | 0.064 | 0.312 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.022 | 0.028 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.011 | 0.008 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.045 | 0.018 |
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".