PONE-D-24-30693Algorithm, Expert, or Both? Evaluating the Role of Feature Selection Methods on User Preferences and ReliancePLOS ONE

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Reviewer #1: Yes

Reviewer #2: Yes

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

Reviewer #1: Yes

Reviewer #2: Yes

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Reviewer #1: Yes

Reviewer #2: Yes

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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: 1.Very well written paper, over all good work , highly satisfactory analysis but I think scope of improvement in presented approach as the approach needs refinement and still lacks of novelty, it is application of existing approaches , no significant innovative contribution from authors side , we would like to listen in this regard from authors side .

2. These few recent state-of-the-art studies should be discussed where human disease prediction related problems have been thoroughly discussed using feature selection (Feature subset selection through nature inspired computing for efficient glaucoma classification from fundus images;Efficient feature selection based novel clinical decision support system for glaucoma prediction from retinal fundus images;A novel hybrid robust architecture for automatic screening of glaucoma using fundus photos, built on feature selection and machine learning-nature driven computing;An enhanced and efficient approach for feature selection for chronic human disease prediction: A breast cancer study)

Best Regards

Reviewer #2: Paper Title

Algorithm, Expert, or Both? Evaluating the Role of Feature Selection Methods on User Preferences and Reliance

The paper tackles an important and timely topic in the intersection of human-computer interaction and AI transparency. As the demand for explainable AI (XAI) grows, understanding how users prefer to engage with feature selection processes is highly relevant. Moreover, the study contributes to the existing literature by addressing the gap in the interaction between expert-driven and algorithmic feature selection, which has practical implications for AI deployment. Moreover, I have added the following comments to enhance the quality of the work.

Comments:

1. Use of Non-Expert Participants:

o The study utilizes lay participants instead of domain experts, limiting the generalizability of the findings to real-world professional settings where expertise is crucial. Resolve this limitation in the revised manuscript.

2. Limited Scope of Feature Selection Methods:

o The study only considers three feature selection methods (algorithm-based, expert-based, and combined), excluding more advanced techniques like dynamic feature selection or metaheuristic optimization, which could provide a more comprehensive exploration of feature selection strategies. Resolve this limitation in the revised manuscript.

3. Stated Preferences vs. Actual Reliance Discrepancy:

o The study highlights a gap between users' stated preferences and their actual reliance on feature selection methods but does not delve deeply into the cognitive reasons behind this discrepancy.

4. Domain-Specific Results:

o The study shows different results in user reliance between domains (e.g., healthcare vs. sports), but does not thoroughly investigate why domain-specific factors influence these outcomes.

5. Subtle Manipulation of Feature Selection Methods:

o The distinction between the feature selection methods may not have been clear enough to participants, which could dilute the observed effects on decision-making and reliance.

6. Lack of Long-Term User Behavior Analysis:

o The experiment captures short-term interactions with AI and does not assess how user preferences and reliance evolve, missing insights into the long-term dynamics of AI trust.

7. No Real-Time Feedback on Decisions:

o Participants did not receive real-time feedback on their decisions, limiting the understanding of how performance feedback might influence reliance on AI systems.

8. Absence of Task Complexity Analysis:

o The study does not investigate how the complexity of tasks influences user reliance on different feature selection methods, potentially overlooking a key factor that impacts decision-making.

9. Single Decision-Making Context:

o The study uses only two decision-making domains (healthcare and sports), limiting the generalizability of the results across a wider range of industries and decision-making environments.

10. Focus on Binary Decision Tasks:

• The study focuses solely on binary decision tasks, which may not fully capture the complexity of real-world decision-making processes that often involve multiple choices or continuous variables.

11. Discuss the scope and relevance of the following studies in terms of User Preferences and Reliance in your work.

• Tiwari, A., & Chaturvedi, A. (2022). A hybrid feature selection approach based on information theory and dynamic butterfly optimization algorithm for data classification. Expert Systems with Applications, 196, 116621.

• Tiwari, A., & Chaturvedi, A. (2021). A novel channel selection method for BCI classification using dynamic channel relevance. IEEE Access, 9, 126698-126716.

• Tiwari, A., & Chaturvedi, A. (2023). Automatic EEG channel selection for multiclass brain-computer interface classification using multiobjective improved firefly algorithm. Multimedia Tools and Applications, 82(4), 5405-5433.

• Tiwari, A. (2023). A logistic binary Jaya optimization-based channel selection scheme for motor-imagery classification in brain-computer interface. Expert Systems with Applications, 223, 119921.

• Tiwari, A. (2023). A hybrid feature selection method using an improved binary butterfly optimization algorithm and adaptive β–hill climbing. IEEE Access, 11, 93511-93537.

• Yin, L., Wang, L., Lu, S., Wang, R., Ren, H., AlSanad, A.,... Zheng, W. (2024). AFBNet: A Lightweight Adaptive Feature Fusion Module for Super-Resolution Algorithms. Computer Modeling in Engineering & Sciences , 140(3), 2315-2347. doi: https://doi.org/10.32604/cmes.2024.050853

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Reviewer #1: No

Reviewer #2: Yes: Dr. Anurag Tiwari

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Submitted filename: Revisions.docx

PONE-D-24-30693R1Algorithm, Expert, or Both? Evaluating the Role of Feature Selection Methods on User Preferences and ReliancePLOS ONE

Dear Dr. Kornowicz,

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.

Please submit your revised manuscript by Feb 10 2025 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,

Sohaib Mustafa, Ph.D.

Academic Editor

PLOS ONE

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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.

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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: (No Response)

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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

Reviewer #3: Yes

**********

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

Reviewer #2: Yes

Reviewer #3: Yes

**********

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

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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

Reviewer #3: 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: (No Response)

Reviewer #3: Please find my remarks below:

1) Please highlight the novelty of the work.

2) What are the limitations of the work?

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Reviewer #2: Yes: Anurag Tiwari

Reviewer #3: No

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Algorithm, Expert, or Both? Evaluating the Role of Feature Selection Methods on User Preferences and Reliance

PONE-D-24-30693R2

Dear Dr. Kornowicz,

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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Sohaib Mustafa, 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 #3: 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 #3: Yes

**********

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

Reviewer #3: N/A

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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 #3: 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 #3: 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 #3: I am happy with the revisions made to the revised manuscript. The authors have adequately addressed all the queries I raised.

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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 #3: No

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