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Magnetic skyrmions are localized, stable topological magnetic textures that can move and interact with each other like ordinary particles when an external stimulus is applied. The efficient control of the motion of spin textures using spin-polarized currents opened an opportunity for skyrmionic devices such as racetrack memory and neuromorphic or reservoir computing. The coexistence of skyrmions with high topological charge in the same system promises further possibilities for efficient technological applications. In this work, we directly observe dipolar skyrmions and antiskyrmions with arbitrary topological charge in Co/Ni multilayers at room temperature. We explore the dipolar-stabilized spin objects with topological charges of up to 10 and characterize their nucleation process, their energy dependence on the topological charge and the effect of the material parameters on their stability. Furthermore, our micromagnetic simulations demonstrate spin-transfer-induced motion of these spin objects, which is important for their potential device application., Competing Interests: Competing interestsThe authors declare no competing interests., (© The Author(s), under exclusive licence to Springer Nature Limited 2024.)

Introduction: Translating narrative clinical guidelines to computable knowledge is a long-standing challenge that has seen a diverse range of approaches. The UK National Institute for Health and Care Excellence (NICE) Content Advisory Board (CAB) aims ultimately to (1) guide clinical decision support and other software developers to increase traceability, fidelity and consistency in supporting clinical use of NICE recommendations, (2) guide local practice audit and intervention to reduce unwarranted variation, (3) provide feedback to NICE on how future recommendations should be developed., Objectives: The first phase of work was to explore a range of technical approaches to transition NICE toward the production of natively digital content., Methods: Following an initial 'collaborathon' in November 2022, the NICE Computable Implementation Guidance project (NCIG) was established. We held a series of workstream calls approximately fortnightly, focusing on (1) user stories and trigger events, (2) information model and definitions, (3) horizon-scanning and output format. A second collaborathon was held in March 2023 to consolidate progress across the workstreams and agree residual actions to complete., Results: While we initially focussed on technical implementation standards, we decided that an intermediate logical model was a more achievable first step in the journey from narrative to fully computable representation. NCIG adopted the WHO Digital Adaptation Kit (DAK) as a technology-agnostic method to model user scenarios, personae, processes and workflow, core data elements and decision-support logic. Further work will address indicators, such as prescribing compliance, and implementation in document templates for primary care patient record systems., Conclusions: The project has shown that the WHO DAK, with some modification, is a promising approach to build technology-neutral logical specifications of NICE recommendations. Implementation of concurrent computable modelling by multidisciplinary teams during guideline development poses methodological and cultural questions that are complex but tractable given suitable will and leadership., Competing Interests: Several authors work in companies that provide computable knowledge products, related data science services, patient record systems and healthcare technology consultancy: Elia Lima‐Walton and Klara Brunnhuber (Elsevier Ltd), Polly Shepperdson (First Data Bank UK Ltd), Ben McAlister (Oracle Health), Charlie McCay (Ramsey Systems), Mark Thomas (Medicaite Ltd) and Justin Whatling (Palantir Technologies Inc.). Several authors work in NICE: Susan Faulding, Felix Greaves, Michaela Heigl, Shaun Rowark and Justin Whatling. Two authors are involved in standards‐development bodies: Charlie McCay (PRSB) and Ben McAlister (HL7 UK). Philip Scott is co‐chair of MCBK‐UK. No author received funding for this project., (© 2023 The Authors. Learning Health Systems published by Wiley Periodicals LLC on behalf of University of Michigan.)