Evidence map›Paper›PMID 41924712›Full record

ArticleJournal of technical writing and communication2025

Synthetic Genres: Expert Genres, Non-Specialist Audiences, and Misinformation in the Artificial Intelligence Age.

Brad Mehlenbacher, Ana Patricia Balbon, Ashley Rose Mehlenbacher

Abstract read
In one paragraph

Article in Journal of technical writing and communication, 2025. 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

3 authors.

Brad MehlenbacherDepartment of English Language and Literature, University of Waterloo, Hagey Hall of the Humanities, 200 University Ave, Waterloo, Ontario, N2L 3G1, Canada.
Ana Patricia BalbonDepartment of Physiology, University of Toronto, Medical Sciences Building, 1 King's College Circle, Toronto, Ontario M5S 1A8, Canada.
Ashley Rose MehlenbacherDepartment of English Language and Literature, University of Waterloo, Hagey Hall of the Humanities, 200 University Ave, Waterloo, Ontario, N2L 3G1, Canada.ORCID https://orcid.org/0000-0003-3471-9008

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Drawing on rhetorical genre studies, we explore research article abstracts created by generative artificial intelligence (AI). These synthetic genres-genre-ing activities shaped by the recursive nature of language learning models in AI-driven text generation-are of interest as they could influence informational quality, leading to various forms of disordered information such as misinformation. We conduct a two-part study generating abstracts about (a) genre scholarship and (b) polarized topics subject to misinformation. We conclude with considerations about this speculative domain of AI text generation and dis/misinformation spread and how genre approaches may be instructive in its identification.

Indexed as

artificial intelligencemisinformationscience communicationsynthetic genres

Identifiers

PMID41924712
PMCPMC13038151

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.