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Alice Oh

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Articles

Build with React on Salesforce: Multi-Framework Is Now GA

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By Charles Watkins, Alice Oh
| sforce.co
Salesforce Multi-Framework is a framework-agnostic runtime on the Headless 360 Platform. Build React apps natively on Salesforce, query records with GraphQL, invoke Apex, and read user context through the UI APIs — no authentication or token management required. You get Salesforce’s security and governance model, plus React’s ecosystem, in one runtime. Launched in open beta earlier this year, Salesforce Multi-Framework is now generally available.
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A reporting checklist for large language models in behavioural science

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By Stefan Feuerriegel, Christopher Barrie, M. J. Crockett, Laura K. Globig, Killian McLoughlin, Dan-Mircea Mirea, Arthur Spirling, Diyi Yang, Tim Althoff, Maria Antoniak, Lisa P. Argyle, Ashwini Ashokkumar, Mohammad Atari, Hannah Bailey, Kevin Bauer, Umang Bhatt, Yidong Chai, Tanmoy Chakraborty Verified, Yanto Chandra, Huimin Chen, Hal Daumé III, Gianmarco De Francisci Morales, Morteza Dehghani, Danica Dillion, Johannes C. Eichstaedt, Kerstin Förster, Dominique Geissler, Kurt Gray, Thomas L. Griffiths, Hartmann Jochen, Oliver Hauser, James He, Rahul Hemrajani, Felix Holzmeister, Angel Hsing-Chi Hwang, Tiancheng Hu, Anna Ivanova, Nils Köbis, Yara Kyrychenko, Himabindu Lakkaraju, Jia Liu, Abdurahman Maarouf, Sebastian Maier, Lennart Meincke, Rada Mihalcea, Brent Mittelstadt, Saif M. Mohammad, Mor Naaman, Oded Netzer, Alice Oh, Desmond C. Ong, Francesco Pierri, Barbara Plank, Iyad Rahwan, Talal Rahwan, Pooja Rao, Claire Robertson, David Rothschild, Matthew Salganik, Eric Schulz, Chirag Shah, Yash Shrestha, Ekaterina Shutova, Alexandra Siegel, Almog Simchon, Huan Sun, Malte Toetzke, Jay Van Bavel, Michelle Vaccaro, Jennifer Vaughan, Effy Vayena, Pedro O. S. Vaz-de-Melo, Briana Vecchione, Angelina Wang, Robert West, Robb Willer, Dirk U. Wulff, Renwen Zhang, Simone Zhang, Steve Rathje, Manoel Horta Ribeiro
| Nature Verified
Large language models offer new opportunities for behavioural science, but their rapid evolution poses challenges for research rigour. We introduce a consensus-based reporting checklist to improve transparency, reproducibility and ethical accountability of large-language-model-based research in the behavioural sciences. You have full access to this article via your institution.
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Artificial intelligence to support cross-disciplinary climate change research

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By Yang Ou, Carlos Rodriguez-Pardo, Alaa Al Khourdajie, Joeri Rogelj, Peijie Zhou, S. Karthik Mukkavilli, Massimo Tavoni, Leon E. Clarke, Yong Liu, Tengjiao Wang, Alice Oh, Haewon McJeon
| Nature Verified
Integrating knowledge across climate risks, societal responses and their interactions is a critical yet persistently challenging goal. We argue that advanced artificial intelligence frameworks, specifically foundation models, offer a new opportunity to unify these domains and support climate decision-making.
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