Evidence map›Paper›PMID 37327133›Full record

ArticleZdravstveno varstvo2023

New Challenges in Scientific Publications: Referencing, Artificial Intelligence and ChatGPT.

Igor Švab, Zalika Klemenc-Ketiš, Saša Zupanič

Abstract readEditorial
In one paragraph

Article in Zdravstveno varstvo, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

  1. Article
  2. Article
  3. ChatGPT and Medical Research: A Meta-Synthesis of Opportunities and Challenges.Journal of advances in medical education & professionalism · 2024
    Review
  4. Article
  5. Article
  6. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Igor ŠvabDepartment of Family Medicine, Medical Faculty, University of Ljubljana, Poljanski nasip 58, 1000 Ljubljana, Slovenia.ORCID https://orcid.org/0000-0003-1303-4974
Zalika Klemenc-KetišDepartment of Family Medicine, Medical Faculty, University of Ljubljana, Poljanski nasip 58, 1000 Ljubljana, Slovenia.ORCID https://orcid.org/0000-0002-0270-1754
Saša ZupaničNational Institute of Public Health, Trubarjeva 2, 1000 Ljubljana, Slovenia.ORCID https://orcid.org/0000-0002-7378-9976

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The COVID-19 pandemic has led to a surge in scientific publications, some of which have bypassed the usual peer-review processes, leading to an increase in unsupported claims being referenced. Therefore, the need for references in scientific articles is increasingly being questioned. The practice of relying solely on quantitative measures, such as impact factor, is also considered inadequate by many experts. This can lead to researchers choosing research ideas that are likely to generate favourable metrics instead of interesting and important topics. Evaluating the quality and scientific value of articles requires a rethinking of current approaches, with a move away from purely quantitative methods. Artificial intelligence (AI)-based tools are making scientific writing easier and less time-consuming, which is likely to further increase the number of scientific publications, potentially leading to higher quality articles. AI tools for searching, analysing, synthesizing, evaluating and writing scientific literature are increasingly being developed. These tools deeply analyse the content of articles, consider their scientific impact, and prioritize the retrieved literature based on this information, presenting it in simple visual graphs. They also help authors to quickly and easily analyse and synthesize knowledge from the literature, prepare summaries of key information, aid in organizing references, and improve manuscript language. The language model ChatGPT has already greatly changed the way people communicate with computers, bringing it closer to human communication. However, while AI tools are helpful, they must be used carefully and ethically. In summary, AI has already changed the way we write articles, and its use in scientific publishing will continue to enhance and streamline the process.

Indexed as

Artificial intelligenceChatGPTPeer reviewReferencingResearch assessmentScientific articles

Identifiers

PMID37327133
PMCPMC10263368

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.