Peer review 1

[demainwang]

Summary This paper investigates the relationship between temperature and cherry blossom bloom duration in Japan using a dual model approach. By combining historical and modern data from satellite imagery, the study analyzes how geographic location and temporal factors influence bloom timing through temperature changes, focusing particularly on predicting bloom duration and temperature patterns.

Strong positive points

1. Comprehensive methodology using two complementary models that analyze both temperature's direct effects and geographic and temporal influences
2. Thorough data processing and analysis, with clear documentation of data cleaning steps and variable selection
3. Excellent visualization of results through well designed figures showing relationships between key variables Strong theoretical foundation linking environmental factors to bloom dynamics.
4. Well structured folder directory, deleted the unnecessary files and properly assign the files

Critical improvements needed

1. Abstract section needs development - currently lacks detail about specific findings and methodology Introduction section is incomplete, missing clear research objectives and literature review
2. Model sections lack proper justification for chosen variables and alternative model comparisons
3. Results interpretation needs expansion, especially regarding real world implications
4. Missing content table indicates the section information.
5. Readme's title not updated, does not match the paper content

Suggestions for improvement

1. Strengthen the abstract by including key findings and methodological approach
2. Expand introduction with comprehensive literature review and clear research objectives
3. Add detailed explanations for model selection and variable choices
4. Include more interpretation of results and their practical implications
5. Update readme title

Evaluation: R/Python cited: 1/1 pts R properly cited Data cited: 1/1 Data properly cited. Class paper: 1/1 LLM documentation: 1/1 Well structured LLM folder. Title: 2/2 Informative Author, date, and repo: 2/2 Abstract: 2/4 Need more precise refinement. Introduction: 3/4 Informative but can be more specific in result paragraph Informative Estimand: 1/1 Data: 7/10 Measurement: 3/4 Model: 7/10 Strong dual model approach. Results: 7/10 Discussion: 7/10 Prose: 5/6 Cross-references: 1/1 Captions: 2/2 Graphs/tables/etc: 4/4 Surveys, sampling, and observational data appendix: 7/10 Include survey, idealized methodology Referencing: 4/4 Commits: 2/2 Sketches: 1/2 Not sure it is suitable to draw all graph in one page Simulation: 4/4 Test:4/4 Parquet: 1/1 Reproducible workflow: 4/4 Enhancements: 0/4 Not data sheet or model card. Miscellaneous:0/3 Estimated overall mark: 93 out of 112 Any other comments: Paper use strong dual model to predict the useful sakura florescence date, with high quality visualization, just remember to update readme's title.

[ShaotongLi-Max]

thanks for your peer view! I nearly forgot to change the readme's title XD, will update soon