PONE-D-23-20544Machine learning-based prediction of distance metastasis risk in invasive ductal carcinoma of the breastPLOS ONE

Dear Dr. Zhang,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

==============================

ACADEMIC EDITOR: Please revise and resubmit your manuscript.  

==============================

Please submit your revised manuscript by Sep 23 2023 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

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If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

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We look forward to receiving your revised manuscript.

Kind regards,

Kathiravan Srinivasan

Academic Editor

PLOS ONE

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4. Please clarify the Figure 8 "Fig 8. Receiver operating characteristic of each prediction model" in page "15" and Figure 8 "Fig 8. Box plot of mean and standard deviation for each indicator" in page "15".

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Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Partly

Reviewer #2: Partly

Reviewer #3: Yes

Reviewer #4: Partly

Reviewer #5: No

Reviewer #6: Partly

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2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: No

Reviewer #2: N/A

Reviewer #3: Yes

Reviewer #4: Yes

Reviewer #5: No

Reviewer #6: I Don't Know

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3. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

Reviewer #4: Yes

Reviewer #5: No

Reviewer #6: No

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4. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: No

Reviewer #2: Yes

Reviewer #3: Yes

Reviewer #4: Yes

Reviewer #5: Yes

Reviewer #6: No

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5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: The study's results were affected by the restricted data availability in terms of regional representation, limited quantity, and subjective feature selection.

-In the context of limited data in this study, data augmentation can be a valuable technique to overcome the scarcity of samples and improve the performance of machine learning models. Data augmentation involves creating additional training examples by applying various transformations to the existing data, while preserving the label information.

For your study, in the case of breast cancer data, data augmentation techniques can be applied to medical images (such as mammograms or MRI scans) to create new images with subtle modifications. These modifications may include rotation, flipping, zooming, translation, or adding noise, among others. By applying such transformations, the dataset can be expanded, enabling the models to learn from a broader range of scenarios.

-In addition to addressing the issue of overfitting, it is essential to thoroughly investigate and fine-tune your model's learning rates.

Reviewer #2: Journal: PLOS ONE

Manuscript Title: Machine learning-based prediction of distance metastasis risk in invasive ductal carcinoma of the breast

Manuscript ID: PONE-D-23-20544

Submission Date: Sunday, July 30, 2023

The manuscript presented “a prediction approach of distance metastasis risk in invasive ductal carcinoma of the breast”. However, the major and critical weak points are that:

(1)Their proposed work discussion is weak distributed to be described or analyzed.

(2)The novelty is not guaranteed.

(3)Their experiments leak from the descriptive and statistical analysis.

The rest of my review presents other weak points, comments, and opinions in detail.

Overall Comments:

(1)[KEYWORDS] The keywords (i.e., index terms) should be sorted in alphabetical order.

(2)[ABSTRACT] The abstract should contain the best-achieved results from the performed experiments.

(3)[ABSTRACT] The abstract should reflect the contributions of the manuscript. I suggest rewriting it.

(4)[INTRODUCTION] The authors should provide a clear problem definition and contributions in the introduction section.

(5)[RESEARCH QUESTION] Where is the research question and research gap?

(6)[RESEARCH QUESTION] The research question is not well-formulated or is poorly motivated, and the paper does not provide new insights or information that is not already known.

(7)[RELATED WORK] Where are the related studies? They should be declared in a separate section.

(8)[RELATED WORK] A table of comparisons should be added at the end of the related studies section to praise the pros. and cons. of them. The year column should be added and they should be ordered by it.

(9)[EQUATIONS] The authors should follow the journal authors’ guidance in writing the equations, symbols, and variables. Please, refer to the authors guidelines on the journal official website.

(10)[EQUATIONS] Where are the equations of the used metrics?

(11)[DATASETS] Samples from the used dataset should be added and annotated.

(12)[METHODOLOGY] The suggested approach is not clearly discussed. More scientific details should be added.

(13)[METHODOLOGY] What are the used equations in the suggested approach? In other words, how the suggested approach is derived?

(14)[METHODOLOGY] Where is the overall pseudocode? Flowchart? of the suggested approach?

(15)[EXPERIMENTS] The working environment (i.e., software and hardware) should be declared and added to a table.

(16)[EXPERIMENTS] The experimental configurations (i.e., settings) should be declared and added to a table.

(17)[EXPERIMENTS] What are the criteria for selecting the experimental configurations?

(18)[EXPERIMENTS] More experiments should be conducted using different configurations.

(19)[EXPERIMENTS] Where is the tabular representation of the reported results?

(20)[EXPERIMENTS] Why did not the authors compare their approach with others in a table?

(21)[EXPERIMENTS] Why did not the authors compare their approach with another approach to compare the suggested approach efficiency and applicability?

(22)[EXPERIMENTS] Where is the detailed and statistical discussion of the reported results?

(23)[EXPERIMENTS] More experiments should be conducted using a different dataset to prove the generalization.

(24)The manuscript does not provide a clear contribution to the field of research.

(25)The manuscript does not provide a clear justification for the research.

(26)[RESULTS] The authors have not provided adequate visual aids, such as graphs or tables, to help readers understand the data.

(27)[ABBREVIATIONS] The authors should add a table of abbreviations in the revised manuscript.

(28)[SYMBOLS] The authors should add a table of symbols in the revised manuscript.

(29)[CONCLUSIONS] The conclusions in this manuscript are primitive. Please, write your conclusions.

(30)[REFERENCES] There are no citations for many sentences in the manuscript. Why? Please check.

(31)[REFERENCES] The references should be written in the same style following the journal authors’ guidance.

(32)[REFERENCES] Recent citations from 2021 and 2022 should be added to the manuscript.

(33)[PROOFING] The authors should get editing help from someone with full professional proficiency in English.

(34)[PROOFING] The manuscript should be checked again to fix any typos such as missing spaces and commas.

(35)[CONSISTENCY] The manuscript structure is too short. It must be elaborated in their applied technology as should support more rigorous technical aspects.

(36)[CONSISTENCY] Some paragraphs are wrapped in more than 10 lines. They should be split concisely.

(37)[NOVELTY] What is the novelty of the suggested approach?

(38)[LIMITATIONS] What are the limitations of the current study? It should be added in a separate section.

For the authors in case of the authors got a chance to review the manuscript and submit the revised one after the editor’s decision, please, provide a table in the revised manuscript mentioning (1) the comment, (2) the authors’ response, and (3) the authors’ change (if applicable). Please, consider all of the comments and don’t ignore any of them.

Please, refer to the attached file "PONE-D-23-20544 Reviewer.pdf" for the same comments in an organized format.

Reviewer #3: Considering the type of study that is retrospective, the project has no ethical problems.

Your project is excellent and I hope that it will increase the life expectancy of cancer patients in the future.

Reviewer #4: First of all, I would like to thanks authors for the efforts they made to make this contribution. The subject is very interesting and has a very relevant impact on society.

Authors try to deal with the metastasis risk in invasive ductal carcinoma of the breast using machine learning techniques,

We have many questions and remarks about the contribution :

- The paper is well-written and easily understandable.

- Authors gave a big part to the Model's definition and presentation, We think they should revisit this part to make it smaller, all the used algorithms are well known.

- A part of the dataset presentation is essential to simplify the problem understanding and make the model's interpretation significant and efficient.

- Are all features important? If Yes why? If No why authors didn't look for a features selection method to optimize the learning process and complexity?

- We think that the authors have to explain more about the added value and the importance of using machine learning in this problem and how their solution can help doctors.

- We recommend that the literature review be in a table containing recent works on the same topics, used models, results, and limitations

- Authors have to present all models configuration, that make the research reproduction possible

- All used features should be clearly presented

- We recommend the use of a schema to present the research process

Wishing all the best for the upcoming research

Reviewer #5: The overall idea of the manuscript to predict the risk of distant organ metastases is good, but the manuscript is not written well and has some flaws:

- The authors did not provide a list of features used to train their model. They need to show the name, type, and specification of features in a table.

- The authors mentioned that they used an 8:2 ratio to split the database into train/test sets, but they did not report any results on the model's performance on the 20% unseen test dataset.

- The authors mentioned in some parts of the manuscript that their original dataset was unbalanced, and they used an undersampling approach to address this issue. However, they did not provide any information on the original size of the dataset or the size of the dataset after downsampling.

- In line 114, the authors mentioned that they used a "small number of features" to train their model. What are the names of these features? They need to be shown in a table.

- The authors claimed that they wanted to predict the "risk" of distant metastases, yet it seems that the models they trained are binary models that have 0/1 output. Usually, for risk prediction, the model needs to have a continuous output to show the probability of an event.

- In Figure 4, what do M0 and M1 represent?

- In Figure 5, the details of the features need to be made clear in a table, as mentioned in the comment above.

- In Figure 6, the confusion matrix needs to be shown in normalized form to make it more readable.

- In Figure 8, a table should be used instead of a figure.

- In line 249, the authors mentioned that they ranked the importance of 14 features. How did they choose these 14 features?

- In line 327, the authors mentioned that there are a few studies that have done the same work. They should reference these studies in their manuscript and compare their approach with theirs.

Reviewer #6: The authors used random forest, XGBoost, logical regression, and support vector machine (SVM) to construct risk prediction models to build a fusion model based on the voting mechanism to develop a prediction model to determine the risk of distant organ metastasis in invasive ductal carcinoma (IDC). Several concerns are raised with this research that should be considered by the authors.

(1)This article's main concern is its innovation. In what way does this research innovate? There have been a lot of studies using the mentioned machine learning models, and the idea of voting is not new. What makes the introduced method superior?

(2)As I read the article, my initial thought was to find a reason, based on the topic's attractiveness, why this article might attract readers. Unfortunately, I didn't find the article to be well organized and I was not justified in reading it.

(3)Despite the fact that a lot of research has been conducted in this field, the authors did not compare other methods. As a result, it cannot be justified.

(4)The abstract of the article has not been prepared properly. The abstract should begin with a short introduction containing the assumption and challenge of the problem, followed by the proposed method to solve the problem, the results (quantitatively and qualitatively), and the conclusion.

(5)There is a lack of clarity and depth in the introduction related work. The authors should organize them professionally. Furthermore, the references are outdated.

(6)Does the authors' assertion that they implemented the method on this dataset justify the method's generalizability?

(7)Results are poorly presented. Can the classification process be affected by changing parameters? Both qualitative and quantitative results are desired by the reader.

(8)The article should be carefully revised by the authors and possible typos and writing errors should be corrected.

(9)In order to understand the disadvantages of the proposed method, it is recommended to include some figures showing that the proposed method does not produce the expected results. It is also better to mention the disadvantages of the proposed method.

(10)The figures (e.g., Figures 8 and 10) are of poor quality. The authors should include more high-quality figures in the text. It is possible to save images in EMF format to ensure better quality.

(11)There will be a better version of this work with better preparation, such as comparative results, different method output figures, etc.

(12)The article appears to have been written in a hurry, has a low level of innovation, and unfortunately, the professor supervisor did not check the article thoroughly. Although this research has some basic flaws, I believe it still faces some basic challenges.

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6. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

Reviewer #2: Yes: Hossam Balaha

Reviewer #3: No

Reviewer #4: No

Reviewer #5: No

Reviewer #6: No

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Attachments

Attachment

Submitted filename: PONE-D-23-20544 Reviewer.pdf

Attachment

Submitted filename: PONE-D-23-20544_reviewer (3).pdf

PONE-D-23-20544R1Machine learning-based prediction of distant metastasis risk in invasive ductal carcinoma of the breastPLOS ONE

Dear Dr. Zhang,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

==============================

ACADEMIC EDITOR: Please revise and resubmit your manuscript.. 

==============================

Please submit your revised manuscript by Dec 08 2023 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

• A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.
• A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.
• An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: https://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols. Additionally, PLOS ONE offers an option for publishing peer-reviewed Lab Protocol articles, which describe protocols hosted on protocols.io. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols.

We look forward to receiving your revised manuscript.

Kind regards,

Kathiravan Srinivasan

Academic Editor

PLOS ONE

Journal Requirements:

Please review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references. Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript. If you need to cite a retracted article, indicate the article’s retracted status in the References list and also include a citation and full reference for the retraction notice.

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #2: All comments have been addressed

Reviewer #3: All comments have been addressed

Reviewer #5: All comments have been addressed

Reviewer #6: All comments have been addressed

**********

2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #2: Yes

Reviewer #3: Yes

Reviewer #5: Partly

Reviewer #6: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #2: No

Reviewer #3: I Don't Know

Reviewer #5: Yes

Reviewer #6: I Don't Know

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #2: Yes

Reviewer #3: Yes

Reviewer #5: No

Reviewer #6: No

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #2: Yes

Reviewer #3: Yes

Reviewer #5: No

Reviewer #6: Yes

**********

6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #2: Journal: PLOS ONE

Manuscript Title: Machine learning-based prediction of distant metastasis risk in invasive ductal carcinoma of the breast

Manuscript ID: PONE-D-23-20544R1

Submission Date: Monday, October 9, 2023

The authors have made a suitable major revision. However, there are some concerns that should be addressed:

Overall Comments:

(1)The conclusions need to be enhanced and the future work should be addressed.

(2)The statistical analysis should be more descriptive.

(3)The following references can be addressed in your study:

a.Balaha, H. M., Antar, E. R., Saafan, M. M., & El-Gendy, E. M. (2023). A comprehensive framework towards segmenting and classifying breast cancer patients using deep learning and Aquila optimizer. Journal of Ambient Intelligence and Humanized Computing, 14(6), 7897-7917.

b.Lee, S. E., Yoon, J. H., Son, N. H., Han, K., & Moon, H. J. (2023). Screening in Patients With Dense Breasts: Comparison of Mammography, Artificial Intelligence, and Supplementary Ultrasound. American Journal of Roentgenology.

c.Baghdadi, N. A., Malki, A., Balaha, H. M., AbdulAzeem, Y., Badawy, M., & Elhosseini, M. (2022). Classification of breast cancer using a manta-ray foraging optimized transfer learning framework. PeerJ Computer Science, 8, e1054.

For the authors in case of the authors got a chance to review the manuscript and submit the revised one after the editor’s decision, please, provide a table in the revised manuscript mentioning (1) the comment, (2) the authors’ response, and (3) the authors’ change (if applicable). Please, consider all of the comments and don’t ignore any of them.

Please, refer to the attached file "PONE-D-23-20544R1 Reviewer.pdf" for the same comments in an organized format.

Reviewer #3: According to the corrections that were suggested by different reviewers , this article seems to be suitable for publishing.

Reviewer #5: Thanks. I didn't see the "data availability" exploitation in the manuscript. That would be good to add a statement in the manuscript to show how readers can access to the data.

Reviewer #6: There have been many solutions to the previous problems. The authors should take care that the responsibility for the results and validation of the results lies with them alone. Figures and references should be carefully reviewed. The references to the equations, as well as the definitions of some of their parameters, should also be carefully checked.

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7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #2: Yes: Hossam Magdy Balaha

Reviewer #3: No

Reviewer #5: No

Reviewer #6: No

**********

[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.]

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step.

Attachments

Attachment

Submitted filename: PONE-D-23-20544R1 Reviewer.pdf

Machine learning-based prediction of distant metastasis risk in invasive ductal carcinoma of the breast

PONE-D-23-20544R2

Dear Dr. Zhang,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

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If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org.

Kind regards,

Reza Rabiei

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #5: All comments have been addressed

Reviewer #6: All comments have been addressed

**********

2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #5: Yes

Reviewer #6: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #5: Yes

Reviewer #6: I Don't Know

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #5: Yes

Reviewer #6: Yes

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #5: Yes

Reviewer #6: Yes

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6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #5: Thanks for fulfilling the comments. I believe the manuscript is ready to publish in the current format.

Reviewer #6: As a result of the different opinions of the referees and their comments, the article has been significantly improved and is suitable for publication.

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7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

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Reviewer #5: No

Reviewer #6: No

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