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  • × language_ss:"e"
  • × type_ss:"el"
  • × year_i:[2020 TO 2030}
  1. Tay, A.: ¬The next generation discovery citation indexes : a review of the landscape in 2020 (2020) 0.01
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    Date
    17.11.2020 12:22:59
  2. Machado, L.; Martínez-Ávila, D.; Barcellos Almeida, M.; Borges, M.M.: Towards a moderate realistic foundation for ontological knowledge organization systems : the question of the naturalness of classifications (2023) 0.01
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    Abstract
    Several authors emphasize the need for a change in classification theory due to the influence of a dogmatic and monistic ontology supported by an outdated essentialism. These claims tend to focus on the fallibility of knowledge, the need for a pluralistic view, and the theoretical burden of observations. Regardless of the legitimacy of these concerns, there is the risk, when not moderate, to fall into the opposite relativistic extreme. Based on a narrative review of the literature, we aim to reflectively discuss the theoretical foundations that can serve as a basis for a realist position supporting pluralistic ontological classifications. The goal is to show that, against rather conventional solutions, objective scientific-based approaches to natural classifications are presented to be viable, allowing a proper distinction between ontological and taxonomic questions. Supported by critical scientific realism, we consider that such an approach is suitable for the development of ontological Knowledge Organization Systems (KOS). We believe that ontological perspectivism can provide the necessary adaptation to the different granularities of reality.
  3. Park, J.S.; O'Brien, J.C.; Cai, C.J.; Ringel Morris, M.; Liang, P.; Bernstein, M.S.: Generative agents : interactive simulacra of human behavior (2023) 0.01
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    Abstract
    Believable proxies of human behavior can empower interactive applications ranging from immersive environments to rehearsal spaces for interpersonal communication to prototyping tools. In this paper, we introduce generative agents--computational software agents that simulate believable human behavior. Generative agents wake up, cook breakfast, and head to work; artists paint, while authors write; they form opinions, notice each other, and initiate conversations; they remember and reflect on days past as they plan the next day. To enable generative agents, we describe an architecture that extends a large language model to store a complete record of the agent's experiences using natural language, synthesize those memories over time into higher-level reflections, and retrieve them dynamically to plan behavior. We instantiate generative agents to populate an interactive sandbox environment inspired by The Sims, where end users can interact with a small town of twenty five agents using natural language. In an evaluation, these generative agents produce believable individual and emergent social behaviors: for example, starting with only a single user-specified notion that one agent wants to throw a Valentine's Day party, the agents autonomously spread invitations to the party over the next two days, make new acquaintances, ask each other out on dates to the party, and coordinate to show up for the party together at the right time. We demonstrate through ablation that the components of our agent architecture--observation, planning, and reflection--each contribute critically to the believability of agent behavior. By fusing large language models with computational, interactive agents, this work introduces architectural and interaction patterns for enabling believable simulations of human behavior.
  4. Hobert, A.; Jahn, N.; Mayr, P.; Schmidt, B.; Taubert, N.: Open access uptake in Germany 2010-2018 : adoption in a diverse research landscape (2021) 0.01
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    Content
    This study investigates the development of open access (OA) to journal articles from authors affiliated with German universities and non-university research institutions in the period 2010-2018. Beyond determining the overall share of openly available articles, a systematic classification of distinct categories of OA publishing allowed us to identify different patterns of adoption of OA. Taking into account the particularities of the German research landscape, variations in terms of productivity, OA uptake and approaches to OA are examined at the meso-level and possible explanations are discussed. The development of the OA uptake is analysed for the different research sectors in Germany (universities, non-university research institutes of the Helmholtz Association, Fraunhofer Society, Max Planck Society, Leibniz Association, and government research agencies). Combining several data sources (incl. Web of Science, Unpaywall, an authority file of standardised German affiliation information, the ISSN-Gold-OA 3.0 list, and OpenDOAR), the study confirms the growth of the OA share mirroring the international trend reported in related studies. We found that 45% of all considered articles during the observed period were openly available at the time of analysis. Our findings show that subject-specific repositories are the most prevalent type of OA. However, the percentages for publication in fully OA journals and OA via institutional repositories show similarly steep increases. Enabling data-driven decision-making regarding the implementation of OA in Germany at the institutional level, the results of this study furthermore can serve as a baseline to assess the impact recent transformative agreements with major publishers will likely have on scholarly communication.
  5. DeSilva, J.M.; Traniello, J.F.A.; Claxton, A.G.; Fannin, L.D.: When and why did human brains decrease in size? : a new change-point analysis and insights from brain evolution in ants (2021) 0.01
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    Source
    Frontiers in ecology and evolution, 22 October 2021 [https://www.frontiersin.org/articles/10.3389/fevo.2021.742639/full]