Evidence map›Paper›PMID 42168292›Full record

ArticleScientific reports2026

Hallucination risk and trustworthiness of generative AI systems based on IVMPF-MABAC decision-making strategies.

Bo Hsiao, Zeeshan Ali, Hamza Zafar, Bahaaeldin Abdalla, Kamal Shah, Thabet Abdeljawad

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

6 authors.

Bo HsiaoDepartment of Information Management, National Yunlin University of Science and Technology, 123 University Road, Section 3, Douliu, 64002, Yunlin, Taiwan, R.O.C.
Zeeshan AliDepartment of Information Management, National Yunlin University of Science and Technology, 123 University Road, Section 3, Douliu, 64002, Yunlin, Taiwan, R.O.C.
Hamza ZafarDepartment of Information Management, National Yunlin University of Science and Technology, 123 University Road, Section 3, Douliu, 64002, Yunlin, Taiwan, R.O.C.
Bahaaeldin AbdallaDepartment of Mathematics and Sciences, Prince Sultan University, P.O. Box 11586, Riyadh, Saudi Arabia.
Kamal ShahDepartment of Mathematics and Sciences, Prince Sultan University, P.O. Box 11586, Riyadh, Saudi Arabia.
Thabet AbdeljawadDepartment of Mathematics and Sciences, Prince Sultan University, P.O. Box 11586, Riyadh, Saudi Arabia. tabdeljawad@psu.edu.sa.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Hallucination risk and trustworthiness of a generative artificial intelligence system play an important and vital role in daily-life scenarios. The terms Hallucination risk and trustworthiness are very famous for the generative artificial intelligence techniques to confirm that the final results or outputs are safe, accurate, and reliable for users or customers, particularly in education, finance, and healthcare. The main purpose of this manuscript is to evaluate the best and worst decisions among the decisions of Gemini (Google DeepMind), Copilot (GitHub/Microsoft), LLaMA (Meta), Claude (Anthropic), and ChatGPT (OpenAI) based on the following criteria, such as data privacy, explainability, Hallucination risk, reliability, and bias control. Therefore, the system of interval-valued m-polar fuzzy-multi-attribute border approximation area comparison technique for algebraic information is developed. The invented model is very famous and reliable for coping with awkward and complex information. Therefore, for the valuation or the construction of the derived technique, this study aims to develop the novel technique of interval-valued m-polar fuzzy information and also investigate their operations based on algebraic norms for the construction of the averaging operator and geometric operator. Lastly, this study also works on the analysis of the numerical examples and the implementation of the comparative analysis among proposed and prevailing frameworks to derive the validity and effectiveness of the introduced approaches.

Indexed as

Artificial intelligenceDecision-making techniquesHallucination risksInterval-valued m-polar fuzzy setsMABAC models

Identifiers

PMID42168292
PMCPMC13396351

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.