Social media images of China's terraces by Song Chen (19488280)

“…Geo-tagged images were collected using Weibo cookies and Python-based scraping tools (available at: https://github.com/dataabc/weibo-search). …”

Continental-scale impact of bomb radiocarbon affects historical fossil fuel carbon dioxide reconstruction by Jing Li (21564146)

“…</p><p dir="ltr"><b>Source CO2 data (Mauna Loa).xlsx:</b> CO2 data from Mauna Loa (MLO) which belong to Global Greenhouse Gas Reference Network were used in this study as the background CO2 levels, which available from 1970 to 2020 (https://gml.noaa.gov/ccgg/trends/).14</p><p dir="ltr"><b>Statistical analysis code and data (SI table 1-2,4) folder: </b>It contains the python code, source data and results that conducted the statistical analysis. …”

AMBILE_Shah_Jo_Risalo_Labeled by Abdul Majid Bhurgri Institute of Language Engineering Hyderabad (22197295)

“…</li><li>Open the CSV file using <b>Python</b> or <b>Excel</b>:</li></ol><pre><pre>import pandas as pd <br>df = pd.read_csv("Bhittaipedia Risalo -(25-08-25).csv") <br>print(df.head()) <br></pre></pre><p dir="ltr">The dataset is sourced from the <a href="https://bhittaipedia.org/sur-kalyan/d-1/1" rel="noopener" target="_new"><b>AMBILE Bhittaipedia project</b></a>.…”

Aluminum alloy industrial materials defect by Ying Han (20349093)

“…</p><h2>software</h2><h4><b>Set up the Python environment</b></h4><p dir="ltr">1.Download and install the Anaconda.…”

Can Large Language Models Replace Human Subjects? A Large-Scale Replication of Scenario-Based Experiments in Psychology and Management by Ning Li (18882138)

“…**Statistical Analysis and Visualization**: Generate results and figures - Input: Enhanced datasets - Output: Statistical results and visualizations - Code: Visualization and analysis scripts ## Key Variables The datasets contain the following key variables: - **effect_id**: Unique identifier for each effect - **journal, paper, study**: Source information - **human_size**: Sample size in the original human study - **human_direction/LLM_direction**: Effect direction (pos, neg, multi-group) - **direction**: Whether human and LLM directions match (1=same, 0=different, /=multiplegroup) - **human_effsize/LLM_effsize**: Effect sizes before standardization - **human_p_value/LLM_p_value**: p-values from statistical tests - **human_sig/LLM_sig**: Significance status (sig/nonsig at p < 0.05) - **strict_direction**: Filtered directional variable (1, 0, or NaN) - **Study metadata**: Sample type, platform, variable types, etc. ## Reproduction Instructions To reproduce the analyses: 1. …”

Feature-Engineered Mouse Dynamics Dataset For Anomaly Detection by Dheeraj Reddy (21588170)

“…</p><p dir="ltr">Preprocessing Workflow</p><p dir="ltr">The preprocessing logic performs a comprehensive transformation of the raw data using the following stages:</p><ol><li>Raw Data Ingestion</li></ol><ul><li>Captures the following fields from each mouse event:</li><li><ul><li><code>x</code>, <code>y</code> coordinates</li><li><code>client_timestamp</code> (in milliseconds)</li><li>Mouse <code>button</code> and <code>state</code> (Pressed/Released)</li><li>Active application <code>window</code></li></ul></li><li>Data is sourced from three subdirectories per user: <code>training</code>, <code>internal_tests</code>, and <code>external_tests</code></li></ul><ol><li>Kinematic Feature Computation</li></ol><ul><li>Derives time-dependent physical features:</li><li><ul><li><code>velocity</code>, <code>acceleration</code>, <code>jerk</code>, and <code>curvature</code></li></ul></li><li>Accounts for timestamp anomalies, division-by-zero, and missing values</li><li>Applies directional smoothing and curvature approximation using angular differences</li></ul><ol><li>Session-Based Feature Engineering</li></ol><ul><li>Computes the following per session:</li><li><ul><li><code>session_duration</code>, <code>total_distance</code></li><li><code>num_actions</code>, <code>num_clicks</code>, <code>num_strokes</code></li><li><code>mean_time_per_action</code>, <code>avg_drag_time</code></li></ul></li></ul><ol><li>Statistical Aggregation</li></ol><p dir="ltr">For each derived motion variable, the following descriptors are computed:</p><ul><li><code>mean</code>, <code>std</code>, <code>min</code>, <code>max</code>, <code>median</code>, <code>25th percentile (q25)</code>, <code>75th percentile (q75)</code></li></ul><ol><li>Label Alignment</li></ol><ul><li>Merges session-level features with binary labels from <code>labels.csv</code></li><li><ul><li><code>risk = 0</code>: Normal session</li><li><code>risk = 1</code>: Anomalous session (e.g., unauthorized access)</li></ul></li><li>Ensures every row is traceable via <code>session_name</code></li></ul><ol><li>Output Generation</li></ol><ul><li>Final output: <code>featurized_mouse_data.csv</code></li><li>Includes:</li><li><ul><li>All engineered features</li><li><code>session_name</code>, <code>serial_no.…”

Streamlining a National Flood Assessment using a Flow Scheduler by eRNZ Admin (6438486)

“…This set-up, version controlled using git and deployed on NeSI, provides a robust method for collaborative code development, reproducibility and flexibility.…”

DNA polymerase actively and sequentially displaces single-stranded DNA-binding proteins by Longfu Xu (17298587)

“…It includes force spectroscopy and bulk assay data comparing the activity of wild-type T7 SSB with a C-terminal truncated variant (mut T7 SSB). Code/software The custom-written python scripts for analyzing basepair-time traces, for analyzing the displacement of SSB and for analyzing the real-time DNA primer extension data are available from Github: https://github.com/longfuxu/Interplay_Between_DNAPol_and_SSB, under the MPL-2.0 license. …”

Supplementary Data: Biodiversity and Energy System Planning - Queensland 2025 by Andrew Rogers (17623239)

“…</li><li>Core Tool: CPAs are generated using a custom fork of the source code (released with this Article) supplied by the Multi-criteria Analysis for Planning Renewable Energy (MapRE) initiative.…”

data for PONE-D-25-41664 by Ying Song (22646597)

“…Software Requirements</p><p dir="ltr">This dataset is provided in .xlsx format and can be opened with:</p><p><br></p><p dir="ltr">Statistical software: R, Stata, Python (pandas)</p><p dir="ltr">Spreadsheet programs: Microsoft Excel, Google Sheets, LibreOffice Calc</p><p><br></p><p dir="ltr">8. …”