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  1. Book ; Online: Die Zukunft des MINT-Lernens – Band 1

    Roth, Jürgen / Baum, Michael / Eilerts, Katja / Hornung, Gabriele / Trefzger, Thomas

    Perspektiven auf (digitalen) MINT-Unterricht und Lehrkräftebildung

    2023  

    Author's details herausgegeben von Jürgen Roth, Michael Baum, Katja Eilerts, Gabriele Hornung, Thomas Trefzger
    Keywords Mathematics ; Science—Study and teaching ; Teaching ; Mass media and education
    Subject code 510
    Language German
    Size 1 Online-Ressource (X, 238 S. 48 Abb., 35 Abb. in Farbe)
    Edition 1st ed. 2023
    Publisher Springer Berlin Heidelberg ; Imprint: Springer Spektrum
    Publishing place Berlin, Heidelberg
    Document type Book ; Online
    HBZ-ID HT021682352
    ISBN 978-3-662-66131-4 ; 9783662661307 ; 3-662-66131-4 ; 3662661306
    DOI 10.1007/978-3-662-66131-4
    Database ZB MED Catalogue: Medicine, Health, Nutrition, Environment, Agriculture

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  2. Book ; Online: Die Zukunft des MINT-Lernens – Band 2

    Roth, Jürgen / Baum, Michael / Eilerts, Katja / Hornung, Gabriele / Trefzger, Thomas

    Digitale Tools und Methoden für das Lehren und Lernen

    2023  

    Author's details herausgegeben von Jürgen Roth, Michael Baum, Katja Eilerts, Gabriele Hornung, Thomas Trefzger
    Keywords Mathematics ; Science—Study and teaching ; Teaching ; Mass media and education
    Subject code 510
    Language German
    Size 1 Online-Ressource (XI, 163 S. 47 Abb., 33 Abb. in Farbe)
    Edition 1st ed. 2023
    Publisher Springer Berlin Heidelberg ; Imprint: Springer Spektrum
    Publishing place Berlin, Heidelberg
    Document type Book ; Online
    HBZ-ID HT021736437
    ISBN 978-3-662-66133-8 ; 9783662661321 ; 3-662-66133-0 ; 3662661322
    DOI 10.1007/978-3-662-66133-8
    Database ZB MED Catalogue: Medicine, Health, Nutrition, Environment, Agriculture

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  3. Book ; Online: Die Zukunft des MINT-Lernens - Band 1

    Roth, Jürgen / Roth, Jürgen / Baum, Michael / Eilerts, Katja / Hornung, Gabriele / Trefzger, Thomas

    Perspektiven auf (digitalen) MINT-Unterricht und Lehrkräftebildung

    2023  

    Keywords Mathematics ; Teaching of a specific subject ; Education ; digitaler MINT-Unterricht im 21. Jahrhundert ; MINT-Lehrkräftebildung ; Perspektiven auf digitalen MINT-Unterricht ; Lehramtsstudium MINT ; MINT-Lernen digital ; Computational Thinking
    Language German
    Size 1 electronic resource (238 pages)
    Publisher Springer Nature
    Publishing place Berlin, Heidelberg
    Document type Book ; Online
    Note German
    HBZ-ID HT030379256
    ISBN 9783662661314 ; 3662661314
    Database ZB MED Catalogue: Medicine, Health, Nutrition, Environment, Agriculture

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  4. Book ; Online: Die Zukunft des MINT-Lernens - Band 2

    Roth, Jürgen / Roth, Jürgen / Baum, Michael / Eilerts, Katja / Hornung, Gabriele / Trefzger, Thomas

    Digitale Tools und Methoden für das Lehren und Lernen

    2023  

    Keywords Mathematics ; Teaching of a specific subject ; Education ; digitaler MINT-Unterricht im 21. Jahrhundert ; MINT-Lehrkräftebildung ; Lehramtsstudium MINT ; MINT-Lernen digital ; Computational Thinking ; Digitale Tools für den MINT-Unterricht ; Digitale Methoden im MINT-Unterricht
    Language German
    Size 1 electronic resource (163 pages)
    Publisher Springer Nature
    Publishing place Berlin, Heidelberg
    Document type Book ; Online
    Note German
    HBZ-ID HT030377020
    ISBN 9783662661338 ; 3662661330
    Database ZB MED Catalogue: Medicine, Health, Nutrition, Environment, Agriculture

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  5. Article ; Online: A note to our authors: Histochemistry and Cell Biology implements guidelines for the use of large language models (including ChatGPT).

    Roth, Jürgen

    Histochemistry and cell biology

    2023  Volume 160, Issue 5, Page(s) 375

    Language English
    Publishing date 2023-10-19
    Publishing country Germany
    Document type Editorial
    ZDB-ID 1222930-1
    ISSN 1432-119X ; 0301-5564 ; 0948-6143
    ISSN (online) 1432-119X
    ISSN 0301-5564 ; 0948-6143
    DOI 10.1007/s00418-023-02245-x
    Database MEDical Literature Analysis and Retrieval System OnLINE

    Full text online

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    In stock of ZB MED Cologne/Königswinter

    Ub I Zs.94/a: Show issues Location:
    Je nach Verfügbarkeit (siehe Angabe bei Bestand)
    bis Jg. 2021: Bestellungen von Artikeln über das Online-Bestellformular
    ab Jg. 2022: Lesesaal (EG)

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  6. Article ; Online: In focus in HCB.

    Taatjes, Douglas J / Roth, Jürgen

    Histochemistry and cell biology

    2024  Volume 161, Issue 1, Page(s) 1–3

    Language English
    Publishing date 2024-01-09
    Publishing country Germany
    Document type Editorial
    ZDB-ID 1222930-1
    ISSN 1432-119X ; 0301-5564 ; 0948-6143
    ISSN (online) 1432-119X
    ISSN 0301-5564 ; 0948-6143
    DOI 10.1007/s00418-023-02260-y
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    In stock of ZB MED Cologne/Königswinter

    Ub I Zs.94/a: Show issues Location:
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  7. Article ; Online: In focus in HCB.

    Taatjes, Douglas J / Roth, Jürgen

    Histochemistry and cell biology

    2024  Volume 161, Issue 2, Page(s) 95–97

    Language English
    Publishing date 2024-01-24
    Publishing country Germany
    Document type Editorial
    ZDB-ID 1222930-1
    ISSN 1432-119X ; 0301-5564 ; 0948-6143
    ISSN (online) 1432-119X
    ISSN 0301-5564 ; 0948-6143
    DOI 10.1007/s00418-024-02266-0
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    In stock of ZB MED Cologne/Königswinter

    Ub I Zs.94/a: Show issues Location:
    Je nach Verfügbarkeit (siehe Angabe bei Bestand)
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  8. Article ; Online: In focus in HCB.

    Taatjes, Douglas J / Roth, Jürgen

    Histochemistry and cell biology

    2024  Volume 161, Issue 3, Page(s) 207–209

    Language English
    Publishing date 2024-02-03
    Publishing country Germany
    Document type Editorial
    ZDB-ID 1222930-1
    ISSN 1432-119X ; 0301-5564 ; 0948-6143
    ISSN (online) 1432-119X
    ISSN 0301-5564 ; 0948-6143
    DOI 10.1007/s00418-024-02271-3
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    In stock of ZB MED Cologne/Königswinter

    Ub I Zs.94/a: Show issues Location:
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  9. Article ; Online: In focus in HCB.

    Taatjes, Douglas J / Roth, Jürgen

    Histochemistry and cell biology

    2024  Volume 161, Issue 4, Page(s) 297–298

    Language English
    Publishing date 2024-03-18
    Publishing country Germany
    Document type Editorial
    ZDB-ID 1222930-1
    ISSN 1432-119X ; 0301-5564 ; 0948-6143
    ISSN (online) 1432-119X
    ISSN 0301-5564 ; 0948-6143
    DOI 10.1007/s00418-024-02276-y
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    In stock of ZB MED Cologne/Königswinter

    Ub I Zs.94/a: Show issues Location:
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  10. Article ; Online: Relationship between prediction accuracy and uncertainty in compound potency prediction using deep neural networks and control models.

    Roth, Jannik P / Bajorath, Jürgen

    Scientific reports

    2024  Volume 14, Issue 1, Page(s) 6536

    Abstract: The assessment of prediction variance or uncertainty contributes to the evaluation of machine learning models. In molecular machine learning, uncertainty quantification is an evolving area of research where currently no standard approaches or general ... ...

    Abstract The assessment of prediction variance or uncertainty contributes to the evaluation of machine learning models. In molecular machine learning, uncertainty quantification is an evolving area of research where currently no standard approaches or general guidelines are available. We have carried out a detailed analysis of deep neural network variants and simple control models for compound potency prediction to study relationships between prediction accuracy and uncertainty. For comparably accurate predictions obtained with models of different complexity, highly variable prediction uncertainties were detected using different metrics. Furthermore, a strong dependence of prediction characteristics and uncertainties on potency levels of test compounds was observed, often leading to over- or under-confident model decisions with respect to the expected variance of predictions. Moreover, neural network models responded very differently to training set modifications. Taken together, our findings indicate that there is only little, if any correlation between compound potency prediction accuracy and uncertainty, especially for deep neural network models, when predictions are assessed on the basis of currently used metrics for uncertainty quantification.
    Language English
    Publishing date 2024-03-19
    Publishing country England
    Document type Journal Article
    ZDB-ID 2615211-3
    ISSN 2045-2322 ; 2045-2322
    ISSN (online) 2045-2322
    ISSN 2045-2322
    DOI 10.1038/s41598-024-57135-6
    Database MEDical Literature Analysis and Retrieval System OnLINE

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