PONE-D-24-16061Seismic Hazard Analysis and Financial Assessment of Railway Infrastructure: A Machine Learning ApproachPLOS ONE

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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

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

Reviewer #1: I Don't Know

Reviewer #2: No

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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: No

Reviewer #2: Yes

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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: Yes

Reviewer #2: Yes

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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 authors of the paper touched upon a very important topic. On the one hand, they determined the relationship between the frequency of earthquakes and railroad accidents, and on the other hand, they linked these data to the costs of railroad infrastructure.

However, the methods used by the authors can be called classical. It would be interesting to use modern machine learning methods. It is unclear why the authors, for example, did not use deep neural networks. In my opinion, for publication in a journal of this level, the authors should have conducted a deeper analysis in at least one of the two selected areas.

Comments

1. The manuscript can be divided into two parts. The first part, devoted to establishing the connection between earthquakes and railroad accidents, is technically competent. Classical methods are used, the literacy of which is not in doubt. As for the second part - proposals for the development of railroad infrastructure - I cannot give an assessment.

2. I can't spin off the dataset, so I can't check the validity of the statistical analysis.

3. The authors did not provide full access to all data underlying the results of their manuscript.

4. The manuscript is written in clear language.

Reviewer #2: The manuscript should provide more detailed descriptions of the datasets used. While it mentions the sources (Federal Railroad database and U.S. Geological Survey database), it should include details such as the number of data points from each, time periods covered, and any preprocessing steps taken to refine the inputs to the model.

In terms of experiment set-up, the methodology section should elaborate on control measures - for example, if there were any control variables and/or assumptions made during model training/testing, these should be explicitly stated. Further, while the document captures the split of data into training and validation sets, explaining the approach used (e.g., proportions, randomization methods) would drive transparency. Further, information number of repeated experiments to arrive at the results is also missing. For example, specifying cross-validation techniques/detailing the number of folds will improve the result reliability.

While the manuscript compares different models, it should also provide statistical significance of tests across these models. Including confidence intervals or related metrics will help here.

The details around monte-carlo simulation are also missing - detailing the number of simulations and the distribution of input variables is needed.

Clarification is needed on metrics used for performance evaluation and their suitability for this research - for instance the rationale behind using R-squared, Mean Absolute Error (MAE), and Root Mean Squared Error (RMSE) for model evaluation.

Other general suggestions:

Please provide the definition or citation to technical terms - for instance peak ground acceleration is not defined when it is used first. Similarly, there is lack of consistency in usage of technical terms -seismic variables and earthquake variables are used interchangeably which can create confusion to the reader

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Reviewer #1: Yes: Alexey Osipov

Reviewer #2: Yes: Vineet Gupta

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Seismic Hazard Analysis and Financial Impact Assessment of Railway Infrastructure in the US West Coast: A Machine Learning Approach

PONE-D-24-16061R1

Dear Dr.  Rungskunroch,

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.

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Kind regards,

Ahmed Mancy Mosa, Ph.D.

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 #2: All comments have been addressed

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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

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

Reviewer #2: Yes

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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

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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

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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 #2: The authors have addressed the feedback provided in the previous review and have captured the responses well in the addendum to the submission.

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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: Vineet Gupta

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