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Applied Science and Industrial Research [PDF]
Nature, 1920 YOUR correspondent Mr. J. W. Williamson says in NATURE of May 27 that much of my criticism of the Department of Scientific and Industrial Research “seems to lend colour” to current misconceptions of industrial research, which he proceeds to construct out of his own imagination, having first fathered them on me, and then submits that the cause of pure ...
John Williamson
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Acknowledgment to Reviewers of Applied Sciences in 2021
Applied Sciences, 2022 Rigorous peer-reviews are the basis of high-quality academic publishing [...]
Applied Sciences Editorial Office
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Applied Sciences, 2021 We wish to make the following corrections to the published paper [...]
Applied Sciences Editorial Office
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Acknowledgement to Reviewers of Applied Sciences in 2019
Applied Sciences, 2020 The editorial team greatly appreciates the reviewers who have dedicated their considerable time and expertise to the journal’s rigorous editorial process over the past 12 months, regardless of whether the papers are finally published or not [...]
Applied Sciences Editorial Office
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Erratum: Towards the Quantification of 5f Delocalization. Applied Sciences 2020, 10, 2918
Applied Sciences, 2020 We wish to make the following correction to the published paper [...]
Applied Sciences Editorial Office
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Acknowledgment to the Reviewers of Applied Sciences in 2022
Applied Sciences, 2023 High-quality academic publishing is built on rigorous peer review [...]
Applied Sciences Editorial Office
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Acknowledgment to Reviewers of Applied Sciences in 2020
Applied Sciences, 2021 Peer review is the driving force of journal development, and reviewers are gatekeepers who ensure that Applied Sciences maintains its standards for the high quality of its published papers [...]
Applied Sciences Editorial Office
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Applied Sciences, 2020 We wish to make the following correction to the published paper [1] as Affiliation 2 is incorrect[...]
Applied Sciences Editorial Office
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Trust in Data Science: Collaboration, Translation, and Accountability in Corporate Data Science Projects [PDF]
Proc. ACM Hum.-Comput. Interact. 2, CSCW, Article 136 (November
2018), 28 pages, 2020 The trustworthiness of data science systems in applied and real-world settings emerges from the resolution of specific tensions through situated, pragmatic, and ongoing forms of work. Drawing on research in CSCW, critical data studies, and history and sociology of science, and six months of immersive ethnographic fieldwork with a corporate data science
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