Weekly research radar
A weekly overview of research areas gaining momentum, built from recent papers, topic movement, and Scollr activity.
Reviewed weekly from recent paper activity, topic movement, and reader activity in Scollr.
Concise reads on research areas with enough fresh activity to explain what changed, why it matters, and where to go deeper.
Obesity Pharmacology shows 208 eligible recent papers and 208 commentary-ready papers in the current 30-day window, compared with 132 eligible papers in the prior window. The strongest evidence comes from 1 visible topic cluster and 8 representative papers.
COPD Research shows 476 eligible recent papers and 476 commentary-ready papers in the current 30-day window, compared with 415 eligible papers in the prior window. The strongest evidence comes from 1 visible topic cluster and 8 representative papers.
CAR-T Cell Therapy Research shows 864 eligible recent papers and 854 commentary-ready papers in the current 30-day window, compared with 534 eligible papers in the prior window. The strongest evidence comes from 1 visible topic cluster and 8 representative papers.
4 recent previews shown here; 19 more in the full directory.
Remote Sensing in Agriculture shows 1,026 eligible recent papers and 1,024 commentary-ready papers in the current 30-day window, compared with 824 eligible papers in the prior window. The strongest evidence comes from 1 visible topic cluster and 8 representative papers.
Cancer Immunotherapy and Biomarkers shows 2,290 eligible recent papers and 2,277 commentary-ready papers in the current 30-day window, compared with 1,094 eligible papers in the prior window. The strongest evidence comes from 1 visible topic cluster and 8 representative papers.
AI Ethics and Social Impacts shows 2,154 eligible recent papers and 2,152 commentary-ready papers in the current 30-day window, compared with 1,520 eligible papers in the prior window. The strongest evidence comes from 1 visible topic cluster and 8 representative papers. 1 representative paper is a preprint, so those findings should be treated as preliminary.
Machine Learning in Materials Science shows 1,486 eligible recent papers and 1,484 commentary-ready papers in the current 30-day window, compared with 1,379 eligible papers in the prior window. The strongest evidence comes from 1 visible topic cluster and 8 representative papers. 4 representative papers are preprints, so those findings should be treated as preliminary.
A compact read on papers gaining traction near the same topics.
This short paper addresses the persistent challenge of tacit troubleshooting knowledge loss on the manufacturing shop floor. Existing knowledge management approaches often fail under time pressure and rarely capture the situated experiential reasoning of operators. Building on...
inhomogeneity limits wide adoption for routine fetal imaging. Consequently, most clinical examinations are performed at 1.5T, where greater motion tolerance comes at the cost of lower SNR, reduced gray-white matter contrast, and partial-volume blurring - factors that undermine...
Join Kofi Bazzell-Smith for this hands-on activity on the basics of making manga. You must register for this activity using the event app. A link to register via the app is coming soon!
In a sample representing approximately 802,954 live births from 10 U.S. states, the most common motivations for prenatal cannabis use were for mental health reasons, and alleviation of pregnancy-related symptoms was identified as the most common motivation for use.
Existing descriptions of AI roles in human‑AI collaboration remain inconsistent and often contradictory. For example, some define AI assistants as strictly reactive, while others attribute them with proactive behavior. To address this lack of clarity, we develop a taxonomy tha...
The rise of Large Language Models (LLMs) has enabled agentic AI capable of complex reasoning and tool use; however, deploying such autonomy in pervasive computing environments remains challenging due to the strict memory and energy constraints of embedded microcontrollers. Exi...