#Openaccess

In a landmark shift that began this summer, a policy originally designed to accelerate access to publicly funded science has unleashed a costly cascade for researchers and the publishers who serve them. The latest survey of open-access dynamics shows that making research freely available immediately—while laudable in principle—can come with substantial price tags for authors, funders, and institutions. The story—first reported through researchers who found themselves staring at article-processing charges in the thousands of dollars—highlights a core tension at the heart of modern science: openness versus affordability, and who pays for it.

A new international study shows artificial intelligence is reshaping scientific publishing, with large language models increasingly assisting writing across disciplines. The study, highlighted by Nature Human Behaviour and summarized for the public, reveals that AI-generated text is influencing abstracts and introductions in many fields, including computer science. The shift has sparked excitement for faster writing and concerns about accuracy, originality, and access to AI tools for researchers in non-native English-speaking countries.

In a significant leap for environmental health research, scientists at the University of California, Riverside (UCR) have developed a new computer language called Mass Query Language, or MassQL, which enables researchers to effortlessly sift through vast chemical datasets to detect previously hidden pollutants. This innovative tool, detailed in a recent Nature Methods journal article, has already led to the discovery of toxic compounds in public water sources that had previously gone unnoticed by traditional detection methods (UCR News).

A breakthrough in environmental health research could transform how Thailand detects hidden pollutants. Scientists at the University of California, Riverside have developed Mass Query Language (MassQL), a user-friendly tool that streams through massive chemical datasets to uncover pollutants previously missed by traditional methods. The development is described in Nature Methods, and researchers demonstrated its potential by identifying toxic compounds in public water samples. The discovery was highlighted in UCR’s recent briefing on the project.