Opening statement summary
I am peer-reviewing a paper by John Zhang that analyzes the Toronto Island Ferry Tickets dataset to study passenger flow, with the goal of optimizing ferry operations and scheduling.
Strong positive points
The title and abstract are concise and informative, effectively presenting the key findings from the dataset to the readers.
The paper does a good job at visualization, such as trend in 2023 and monthly trends.
Critical improvements needed
The discussion section is insufficient and should include a deeper analysis. For example, incorporating literature reviews and examining the reasons behind the observed seasonal peak patterns would enhance the discussion.
Suggestions for improvement:
Update the usage of the LLM.
Upload the sketches.
Remove unnecessary starter files from the folder, such as "05-replication" in the scripts folder.
Update the data cleaning files.
Add literature reviews to support your analysis.
Remove the detailed data cleaning steps from the data section, leaving only the critical information.
Evaluation:
Overall, the paper is well-structured and clearly presents the findings.
R is appropriately cited: 1/1
LLM usage is documented: 0/1
Estimated mark:
0 out of 64 (0 out of 100).
Reason:
The main reason is that the LLM usage has not been documented. Besides of this point, the discussion lacks depth analysis. Additionally, the absence of data cleaning scripts makes the data and paper not fully reproducible.
Opening statement summary I am peer-reviewing a paper by John Zhang that analyzes the Toronto Island Ferry Tickets dataset to study passenger flow, with the goal of optimizing ferry operations and scheduling.
Strong positive points
Critical improvements needed The discussion section is insufficient and should include a deeper analysis. For example, incorporating literature reviews and examining the reasons behind the observed seasonal peak patterns would enhance the discussion.
Suggestions for improvement:
Evaluation: Overall, the paper is well-structured and clearly presents the findings.
R is appropriately cited: 1/1 LLM usage is documented: 0/1
Estimated mark: 0 out of 64 (0 out of 100).
Reason: The main reason is that the LLM usage has not been documented. Besides of this point, the discussion lacks depth analysis. Additionally, the absence of data cleaning scripts makes the data and paper not fully reproducible.