Evidence map›Paper›PMID 41735347›Full record

ArticleNPJ science of food2026

AI-mediated risks and real-life challenges in mushroom foraging.

Nik V Kuznetsov, Yu Xia, Sergei Kuznetsov, Fransina Christina King, Milos Ljubisavljevic

Abstract read
In one paragraph

Article in NPJ science of food, 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

5 authors.

Nik V KuznetsovASPIRE Precision Medicine Research Institute Abu Dhabi, United Arab Emirates University, Al Ain, United Arab Emirates. nikkuznetsov@inbox.com.ORCID http://orcid.org/0000-0003-3010-3927
Yu Xia *KTH Royal Institute of Technology, Stockholm, Sweden.
Sergei Kuznetsov *KTH Royal Institute of Technology, Stockholm, Sweden.
Fransina Christina KingASPIRE Precision Medicine Research Institute Abu Dhabi, United Arab Emirates University, Al Ain, United Arab Emirates.ORCID http://orcid.org/0000-0001-7250-5145
Milos LjubisavljevicASPIRE Precision Medicine Research Institute Abu Dhabi, United Arab Emirates University, Al Ain, United Arab Emirates.ORCID http://orcid.org/0000-0002-5025-3562

Funding

ASPIRE, the technology program management pillar of Abu Dhabi's Advanced Technology Research Council (ATRC), via the ASPIRE Precision Medicine Research Institute Abu Dhabi (ASPIREPMRIAD) VRI-20-10
6 · The paper itself

Abstract

The rise of AI-based mushroom identification applications impacts foraging despite significant risks from relying solely on AI-generated advice. Popular AI-based mushroom identification tools were tested using 100+ photos of nearly 60 species, taken in real-world conditions. Even the best-performing tool failed in almost 15% of cases, with others performing worse. None of tested applications consistently provided a single, correct answer, demonstrating they cannot be trusted for definitive life-or-death identification decisions.

Identifiers

PMID41735347
PMCPMC13065802

What Socratic 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 Socratic graph.