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  1. Noever, D.; Ciolino, M.: ¬The Turing deception (2022) 0.11 
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    Date
    1. 1.2023 17:48:50
    Source
    https%3A%2F%2Farxiv.org%2Fabs%2F2212.06721&usg=AOvVaw3i_9pZm9y_dQWoHi6uv0EN
  2. Großjohann, K.: Gathering-, Harvesting-, Suchmaschinen (1996) 0.02 
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    Date
    7. 2.1996 22:38:41
    Pages
    22 S
  3. Wätjen, H.-J.: Mensch oder Maschine? : Auswahl und Erschließung vonm Informationsressourcen im Internet (1996) 0.01 
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    Date
    2. 2.1996 15:40:22
  4. Robertson, S.E.: OKAPI at TREC-1 (1994) 0.01 
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    Abstract
    Describes the work carried out on the TREC-2 project following the results of the TREC-1 project. Experiments were conducted on the OKAPI experimental text information retrieval system which investigated a number of alternative probabilistic term weighting functions in place of the 'standard' Robertson Sparck Jones weighting functions used in TREC-1
  5. Williamson, N.J.: Online Klassifikation : Gegenwart und Zukunft (1988) 0.01 
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    Footnote
    21-CLASS-1-G (dt. Übers.)
  6. Walker, S.: ¬Der Mensch-Maschine-Dialog bei Online-Benutzer-Katalogen (1987) 0.01 
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    Footnote
    17-INF-1-G (dt. Übers.)
  7. Allen, G.G.: Change in the catalogue in the context of library management (1976) 0.01 
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    Footnote
    76-CAT-1-E
  8. Holley, R.P.: Classification in the USA (1985) 0.01 
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    Footnote
    47-CLAS-1-E
  9. Jouguelet, S.: Subject access and the marketplace for bibliographic information in France (1989) 0.01 
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    Footnote
    36-CLASS-1-E
  10. Finni, J.F.; Paulson, P.J.: ¬Die Dewey Decimal Classification kommt in das Computer-Zeitalter : Entwicklung der DDC-Datenbank und des 'Editorial Support System' (1987) 0.01 
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    Footnote
    37-CLAS-1-G (dt. Übers.)
  11. Landry, P.: ¬The MACS project : multilingual access to subject headings (LCSH, RAMEAU, SWD) (2000) 0.01 
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    Date
    1. 4.2002 10:17:10
  12. Luo, L.; Ju, J.; Li, Y.-F.; Haffari, G.; Xiong, B.; Pan, S.: ChatRule: mining logical rules with large language models for knowledge graph reasoning (2023) 0.01 
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    Date
    23.11.2023 19:07:22
  13. McIlwaine, I.C.: UDK: der gegenwärtige Zustand und künftige Entwicklungen (1993) 0.01 
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    Abstract
    Der Vortrag berichtet über die Fertigstellung des maschinenlesbaren Master Reference File der UDK und zeigt, wie er zusammengestellt wurde. Die als Quelle benutzte Ausgaben werden vorgestellt, insbesondere die Internationale Mittlere Ausgabe in Englisch und Französisch, die neuen Abschnitte für Physikalische Chemie und für Sprachen, die in den 'Extensions and corrections to the UDC 14(1992)' veröffentlicht wurden, werden dargestellt und Pläne für die weitere Entwicklung der Systematik auf einer konsequenten facettierten Grundlage entwickelt. Zwei aktuelle Ausgaben, Classification décimale universelle, édition moyenne, Vol.1(1990) und CDU: Classification Decimal Universal, edicion abreviada española (1991) werden besprochen
    Date
    1. 4.2002 13:19:33
  14. Aydin, Ö.; Karaarslan, E.: OpenAI ChatGPT generated literature review: : digital twin in healthcare (2022) 0.00 
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    Abstract
    Literature review articles are essential to summarize the related work in the selected field. However, covering all related studies takes too much time and effort. This study questions how Artificial Intelligence can be used in this process. We used ChatGPT to create a literature review article to show the stage of the OpenAI ChatGPT artificial intelligence application. As the subject, the applications of Digital Twin in the health field were chosen. Abstracts of the last three years (2020, 2021 and 2022) papers were obtained from the keyword "Digital twin in healthcare" search results on Google Scholar and paraphrased by ChatGPT. Later on, we asked ChatGPT questions. The results are promising; however, the paraphrased parts had significant matches when checked with the Ithenticate tool. This article is the first attempt to show the compilation and expression of knowledge will be accelerated with the help of artificial intelligence. We are still at the beginning of such advances. The future academic publishing process will require less human effort, which in turn will allow academics to focus on their studies. In future studies, we will monitor citations to this study to evaluate the academic validity of the content produced by the ChatGPT. 1. Introduction OpenAI ChatGPT (ChatGPT, 2022) is a chatbot based on the OpenAI GPT-3 language model. It is designed to generate human-like text responses to user input in a conversational context. OpenAI ChatGPT is trained on a large dataset of human conversations and can be used to create responses to a wide range of topics and prompts. The chatbot can be used for customer service, content creation, and language translation tasks, creating replies in multiple languages. OpenAI ChatGPT is available through the OpenAI API, which allows developers to access and integrate the chatbot into their applications and systems. OpenAI ChatGPT is a variant of the GPT (Generative Pre-trained Transformer) language model developed by OpenAI. It is designed to generate human-like text, allowing it to engage in conversation with users naturally and intuitively. OpenAI ChatGPT is trained on a large dataset of human conversations, allowing it to understand and respond to a wide range of topics and contexts. It can be used in various applications, such as chatbots, customer service agents, and language translation systems. OpenAI ChatGPT is a state-of-the-art language model able to generate coherent and natural text that can be indistinguishable from text written by a human. As an artificial intelligence, ChatGPT may need help to change academic writing practices. However, it can provide information and guidance on ways to improve people's academic writing skills.

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