Search (163 results, page 1 of 9)

  • × year_i:[2020 TO 2030}
  • × type_ss:"a"
  1. Zilm, G.: "Kl ist ein glorifizierter Taschenrechner" (2023) 0.05
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    Date
    27. 1.2023 16:22:55
  2. Candela, G.: ¬An automatic data quality approach to assess semantic data from cultural heritage institutions (2023) 0.04
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    Date
    22. 6.2023 18:23:31
  3. Geras, A.; Siudem, G.; Gagolewski, M.: Should we introduce a dislike button for academic articles? (2020) 0.03
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    Date
    6. 1.2020 18:10:22
  4. Li, G.; Siddharth, L.; Luo, J.: Embedding knowledge graph of patent metadata to measure knowledge proximity (2023) 0.03
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    Date
    22. 3.2023 12:06:55
  5. Wang, S.; Ma, Y.; Mao, J.; Bai, Y.; Liang, Z.; Li, G.: Quantifying scientific breakthroughs by a novel disruption indicator based on knowledge entities : On the rise of scrape-and-report scholarship in online reviews research (2023) 0.03
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    Date
    22. 1.2023 18:37:33
  6. Yu, C.; Xue, H.; An, L.; Li, G.: ¬A lightweight semantic-enhanced interactive network for efficient short-text matching (2023) 0.03
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    Date
    22. 1.2023 19:05:27
  7. Cerda-Cosme, R.; Méndez, E.: Analysis of shared research data in Spanish scientific papers about COVID-19 : a first approach (2023) 0.03
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    Abstract
    During the coronavirus pandemic, changes in the way science is done and shared occurred, which motivates meta-research to help understand science communication in crises and improve its effectiveness. The objective is to study how many Spanish scientific papers on COVID-19 published during 2020 share their research data. Qualitative and descriptive study applying nine attributes: (a) availability, (b) accessibility, (c) format, (d) licensing, (e) linkage, (f) funding, (g) editorial policy, (h) content, and (i) statistics. We analyzed 1,340 papers, 1,173 (87.5%) did not have research data. A total of 12.5% share their research data of which 2.1% share their data in repositories, 5% share their data through a simple request, 0.2% do not have permission to share their data, and 5.2% share their data as supplementary material. There is a small percentage that shares their research data; however, it demonstrates the researchers' poor knowledge on how to properly share their research data and their lack of knowledge on what is research data.
    Date
    21. 3.2023 19:22:02
  8. Zhang, Y.; Wu, M.; Zhang, G.; Lu, J.: Stepping beyond your comfort zone : diffusion-based network analytics for knowledge trajectory recommendation (2023) 0.03
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    Date
    22. 6.2023 18:07:12
  9. Hindrichs, G.: Kriegszivilgesellschaft (2022) 0.02
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  10. ¬Der Student aus dem Computer (2023) 0.02
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    Date
    27. 1.2023 16:22:55
  11. Jaeger, L.: Wissenschaftler versus Wissenschaft (2020) 0.02
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    Date
    2. 3.2020 14:08:22
  12. Ibrahim, G.M.; Taylor, M.: Krebszellen manipulieren Neurone : Gliome (2023) 0.02
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    Source
    Spektrum der Wissenschaft. 2023, H.10, S.22-24
  13. Noever, D.; Ciolino, M.: ¬The Turing deception (2022) 0.01
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    Source
    https%3A%2F%2Farxiv.org%2Fabs%2F2212.06721&usg=AOvVaw3i_9pZm9y_dQWoHi6uv0EN
  14. Bischoff, M.: KI lernt die Sprache der Mathematik (2020) 0.01
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    Content
    Verweis auf: Lample, G., Charton, F.: Deep learning for symbolic mathematics. ArXiv: 11912.01412, 2019.
  15. Brembs, B.; Förstner, K.; Kraker, P.; Lauer, G.; Müller-Birn, C.; Schönbrodt, F.; Siems, R.: Auf einmal Laborratte (2021) 0.01
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  16. Restrepo, G.: Zeit für eine neue Ordnung? (2022) 0.01
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  17. Knorz, G.: Intellektuelles Indexieren (2023) 0.01
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  18. Buzsaki, G.: Wie das Gehirn die Welt konstruiert (2023) 0.01
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  19. Koch, C.: Was ist Bewusstsein? (2020) 0.01
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    Date
    17. 1.2020 22:15:11
  20. Wagner, E.: Über Impfstoffe zur digitalen Identität? (2020) 0.01
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    Date
    4. 5.2020 17:22:40

Languages

  • e 118
  • d 45

Types