ArticleKnee surgery, sports traumatology, arthroscopy : official journal of the ESSKA2026
Preserving scientific integrity in academic publishing: Navigating artificial intelligence, journal policies and the impact factor as a quality indicator.
Article in Knee surgery, sports traumatology, arthroscopy : official journal of the ESSKA, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- Comment on "Theranostic lipid nanocarriers for precision diagnosis and targeted therapy in pancreatic ductal adenocarcinoma".Journal of cancer research and clinical oncology · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
13 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The integration of artificial intelligence (AI), the rise of mega-journals, and the manipulation of impact factors present challenges to scientific integrity. These trends threaten the core principles of objectivity, reproducibility, and transparency. This editorial highlights two categories of threats: (1) external pressures, such as AI misuse and metric-driven publishing models, and (2) internal systemic flaws, including the 'publish or perish' culture and methodological fragility. Mega-journals, characterized by high-volume publishing and broad interdisciplinary scopes, improve accessibility and accelerate dissemination. However, the emphasis on publication volume might weaken the rigour of peer review. To navigate these challenges, the authors propose a balanced approach that harnesses innovation without compromising scientific integrity. Proposed solutions include mandating AI transparency through frameworks like Consolidated Standards of Reporting Trials-Artificial Intelligence, and redefining impact metrics to emphasize reproducibility, mentorship, and societal impact alongside citations. Scientific journals should promote career opportunities less on publication quantity and more on quality. Global cooperation, via initiatives like the San Francisco Declaration on Research Assessment and the Committee on Publication Ethics, is essential to standardize ethics and address resource disparities. This editorial proposes solutions for researchers, journals, and policymakers to realign academic incentives and uphold the ethical foundation of science. By fostering transparency, accountability, and equity, the scientific community can preserve its ethical foundations while embracing transformative tools, ultimately advancing knowledge and serving society. LEVEL OF EVIDENCE: Level V.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.