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Indonesia holds immense biocultural diversity, yet ethnobotanical data remain fragmented. This systematic review synthesizes medicinal plant use across the archipelago to identify cross-cultural patterns, define a core ethnomedicinal flora, and critically appraise methodological rigor.

Large language models such as ChatGPT are increasingly used by patients seeking perioperative information, yet their reliability for anesthesia-related patient education remains insufficiently evaluated. This study assessed the quality of ChatGPT-4.0 responses to frequently asked anesthesia questions using a multi-rater evaluation framework.

OpenAI Gym is a toolkit for reinforcement learning research. It includes a growing collection of benchmark problems that expose a common interface, and a website where people can share their results and compare the performance of algorithms. This whitepaper discusses the components of OpenAI Gym and the design decisions that went into the software.

We present the OpenAI Remote Rendering Backend (ORRB), a system that allows fast and customizable rendering of robotics environments. It is based on the Unity3d game engine and interfaces with the MuJoCo physics simulation library. ORRB was designed with visual domain randomization in mind. It is optimized for cloud deployment and high throughput operation. We are releasing it to the public under a liberal MIT license: https://github.com/openai/orrb .

Radiologists often employ diagnostic certainty phrases (DCPs) to convey levels of confidence in imaging interpretations. Prior research in adult radiology demonstrated wide variability in DCP usage, potentially complicating communication with clinicians and patients. Little is known about these practices in pediatric radiology. We aimed to characterize DCP use among pediatric radiologists in a large academic institution.

Background/Objectives