Published on in Vol 1, No 1 (2020): Jan-Dec

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/24739, first published .
Author Response to Peer Reviews of “A Machine Learning Explanation of the Pathogen-Immune Relationship of SARS-CoV-2 (COVID-19), and a Model to Predict Immunity and Therapeutic Opportunity: A Comparative Effectiveness Research Study”

Author Response to Peer Reviews of “A Machine Learning Explanation of the Pathogen-Immune Relationship of SARS-CoV-2 (COVID-19), and a Model to Predict Immunity and Therapeutic Opportunity: A Comparative Effectiveness Research Study”

Author Response to Peer Reviews of “A Machine Learning Explanation of the Pathogen-Immune Relationship of SARS-CoV-2 (COVID-19), and a Model to Predict Immunity and Therapeutic Opportunity: A Comparative Effectiveness Research Study”

Authors of this article:

Eric Luellen1, MS, MPH Author Orcid Image

Peer-Review Report

Bioinformatix, Interlochen, MI, United States

Corresponding Author:

Eric Luellen, MS, MPH

Bioinformatix

Faculty Lane, Box 3628

Interlochen, MI, 49643

United States

Phone: 1 4129157468

Email: eluellen@bioinformatix.io



Author response to peer review reports for “A Machine Learning Explanation of the Pathogen-Immune Relationship of SARS-CoV-2 (COVID-19), and a Model to Predict Immunity and Therapeutic Opportunity: A Comparative Effectiveness Research Study.”


Regarding reviewer G’s feedback that the abstract read like bullets to a white paper and was stylistically different, and inferior, to the flow of the main paper, the abstract was revised to be more of a narrative while honoring the mandated structured subheadings. Moreover, the reviewer’s suggestion to include limitations and potential socioeconomic impacts of the results similarly improved the impact of the paper and contextualized its findings. The author is grateful for this insightful feedback because it helped improve the readability of the abstract, and may encourage more researchers, practitioners, and journalists to read the paper. 

Regarding reviewer H’s feedback to be consistent with scientific nomenclature (SARS-CoV-2 or the more colloquial COVID-19), the paper was revised to note the alternative colloquial term once in the title and once in the text, and corrected all entries to the more medically and scientifically correct name, SARS-CoV-2. Again, the author is grateful for this constructive criticism because, in addition to consistency, it may impact readers’ inferences about the training of the author and scientific accuracy of the paper and results.

Edited by G Eysenbach; This is a non–peer-reviewed article. submitted 02.10.20; accepted 02.10.20; published 19.10.20

Copyright

©Eric Luellen. Originally published in JMIRx Med (https://med.jmirx.org), 19.10.2020.

This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the JMIRx Med, is properly cited. The complete bibliographic information, a link to the original publication on https://med.jmirx.org/, as well as this copyright and license information must be included.