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Quantifying effect of Google Scholar on science is hard. Here's one approach: - Assume GS makes old papers (pub'd in 1950-9 or 1960-9) more discoverable, but has little effect on newer papers (pub'd in 1980-4 and 1985-9) - Data: cites to old papers jump when GS released in 2004

The AI x materials fiasco demonstrates why we need much more research about AI x science adoption and impact. This would help to... 1. Satisfy high demand for evidence with rigorous research. 2. Increase resilience to fraud and make it easier to identify suspicious outliers.

🚨 New paper! We present CHIMERA — a KB of 28K+ scientific idea recombinations 💡 It captures how researchers blend concepts or take inspiration across fields, enabling: 1. Meta-science 2. Training models to predict new combos noy-sternlicht.github.io/CHIMERA-Web 👇 Findings & data:

The further a researcher or inventor moves from their previous work, the less cited their latest work will be go.nature.com/454uPfj

Happy to share this timely paper. A thread by my prolific coauthor Dorian Quelle 👇

Nature research paper: The pivot penalty in research go.nature.com/3FemqLN

"𝘐𝘴 𝘈𝘊𝘓 𝘢𝘯 𝘈𝘐 𝘤𝘰𝘯𝘧𝘦𝘳𝘦𝘯𝘤𝘦?" A possible perspective is to examine: "𝘞𝘩𝘪𝘤𝘩 𝘈𝘊𝘓 𝘵𝘰𝘱𝘪𝘤𝘴 𝘳𝘦𝘴𝘰𝘯𝘢𝘵𝘦 𝘣𝘦𝘺𝘰𝘯𝘥 𝘢𝘤𝘢𝘥𝘦𝘮𝘪𝘢 𝘢𝘯𝘥 𝘤𝘢𝘱𝘵𝘶𝘳𝘦 𝘱𝘶𝘣𝘭𝘪𝘤 𝘢𝘵𝘵𝘦𝘯𝘵𝘪𝘰𝘯?" Our #ACL2025 main conf paper delves into this issue. (1/n)

Man, this paints a very grim picture. Oh, and NSF funding rates expected to go from 26% to 7% arstechnica.com/science/2025/0…

LLMs are helpful for scientific research — but will they continuously be helpful? Introducing 🔍ScienceMeter: current knowledge update methods enable 86% preservation of prior scientific knowledge, 72% acquisition of new, and 38%+ projection of future (arxiv.org/abs/2505.24302).