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Review
Peer-Review Record

AI System Engineering—Key Challenges and Lessons Learned

Mach. Learn. Knowl. Extr. 2021, 3(1), 56-83; https://0-doi-org.brum.beds.ac.uk/10.3390/make3010004
by Lukas Fischer 1,*, Lisa Ehrlinger 1,2, Verena Geist 1, Rudolf Ramler 1, Florian Sobiezky 1, Werner Zellinger 1, David Brunner 1, Mohit Kumar 1 and Bernhard Moser 1
Reviewer 1: Anonymous
Reviewer 2: Anonymous
Mach. Learn. Knowl. Extr. 2021, 3(1), 56-83; https://0-doi-org.brum.beds.ac.uk/10.3390/make3010004
Submission received: 3 December 2020 / Revised: 23 December 2020 / Accepted: 25 December 2020 / Published: 31 December 2020
(This article belongs to the Special Issue Selected Papers from CD-MAKE 2020 and ARES 2020)

Round 1

Reviewer 1 Report

Thank you for your manuscript. I enjoyed reading it. To improve its relevance to the readers, please kindly consider the following suggestions:

(1) The focus of the topic is too broad. Therefore, please consider changing the manuscript type from "Article" to "Literature Review" because it is essentially a review of the extant literature. It neither contains any empirical study using artificial intelligence nor does it utilize any primary data.

(2) If this manuscript was intended to be a meta-synthesis of the extant literature, under the Methodology section, please revise your manuscript to describe how it has followed the meta-synthesis framework guidelines, for example, at https://0-journals-sagepub-com.brum.beds.ac.uk/doi/pdf/10.1177/160940690900800304 and/or at https://guides.temple.edu/c.php?g=78618&p=4178716

(3) For the references, instead of formatting "by-hand", please kindly consider using the free Zotero software (https://www.zotero.org/), and select "Multidisciplinary Digital Publishing Institute" as the citation format, since there are 170 citations in your manuscript, and there may probably be more once you have revised the manuscript.

Thank you.

 

Author Response

Dear Reviewer,

Thank you for your kind words and valuable suggestions to improve our manuscript!

We agree that the manuscript type "Literature review" would better suit the content and scope of our paper. Therefore we changed the latex documentclass from "article" to "review". Upon uploading the revised document we will also update the submission type (if possible at that stage) via the submission system.

We do not intend to create a meta-synthesis of the extant literature and therefore also did not follow the respective guidelines.

Concerning your remarks about the references: We use the MDPI Overleaf template and indeed exported all bibtex entries directly from Zotero. Nonetheless we revised all references again for missing fields and updated them accordingly.

Thank you again for your review!

Best regards,

Lukas Fischer

Reviewer 2 Report

A very interesting paper that sums up the main challenges connected to the use of machine learning (DNN in particular) and gives a summary of the authors recent contribution to the field seen in the light of the challenges. The paper has a clear structure once you get a little into it, but the immediate appeal of the paper could relatively easy be raised be communicating the structure much better in the introduction. I'm afraid you may loose a lot of readers here. Otherwise I really like the paper and do not have substantial suggestions for revision. 

 

Two small suggestions for language edits: 

On line 292, page 8: The first "other" should be "on"

On line 418 on page 11: delete the first "most". 

 

Author Response

Dear Reviewer,

Thank you for your kind words and suggestions to improve our manuscirpt!

We agree that due to the amount of information a better overview of the paper structure and content in the introduction would be helpful. We therefore revised the introduction and added an "Outline and Structure" subsection (1.1), giving a brief overview of the following content and structure.

We followed your suggestions and replaced the duplicate "other" in line 292 with "on the". Furthermore we removed the "most" in line 418.

Thank you again for your review!

Best regards,

Lukas Fischer

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