Overview of generalized weighted averages. by Nobuhito Manome (8882084)

“…GWA-UCB1 outperformed G-UCB1, UCB1-Tuned, and Thompson sampling in most problem settings and can be useful in many situations. The code is available at <a href="https://github.com/manome/python-mab" target="_blank">https://github.com/manome/python-mab</a>.…”

PRION Degradome Foundation Atlas by Axel Petzold (7076261)

“…</p><h4><b>Reproducibility</b></h4><p dir="ltr">All datasets can be regenerated using open-source tools (Python, BLAST, SAS). Fully documented Python scripts are included in the repository to ensure transparency, reproducibility, and adaptability across computational environments, following the methodology described in [1].…”

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

“…The project systematically evaluates how GPT-4, Claude, and DeepSeek respond to the same experimental conditions as human participants across multiple psychological studies. ## Project Overview This research investigates whether LLMs can replicate results from human psychological experiments. By presenting LLMs with identical experimental conditions used in the original studies, we compare LLM responses with human responses to assess their understanding of human psychology and potential utility as research tools. …”

Genomic Epidemiology of SARS-CoV-2 in Peru from 2020 to 2024 by Pablo Tsukayama (22614461)

“…<p dir="ltr">This dataset compiles all code, scripts, supporting files, and figure outputs used for the analyses presented in Sobkowiak et al., Genomic Epidemiology of SARS-CoV-2 in Peru, 2020–2024 (Communications Medicine, 2025). …”

Poster: Haplotypes and Human Diversity in Proteomics by Jakub Vasicek (12256415)

“…<p dir="ltr">Poster presented at the GA4GH 2025 conference</p><p dir="ltr">ProHap is a python-based tool built to efficiently generate protein haplotype databases from phased genotypes of reference population panels.…”

<i>In vivo</i> identification of <i>Toxoplasma gondii</i> antigenic proteins and <i>in silico</i> study of their polymorphism. by Julie DENIS (19696753)

“…</li><li><b>MutationRateCalculation.py</b>: Python script for annotating the filtered data.</li><li><b>Analized_variant</b>: Formatted data for variants of interest.…”

entity-poster.pdf by Evgeny Gorbunov (21771560)

“…<p dir="ltr">We update on status of development Entity Toolkit, a next-generation Particle-in-Cell (PIC) code designed to model plasmas in extreme astrophysical environments, such as black hole accretion disks and jets, neutron star magnetospheres, pulsar winds, and intracluster media. …”

LNP drug delivery image data by Philip Harrison (8899735)

“…</div><div><br></div><div><u>Python code:</u></div><div><a href="https://github.com/pharmbio/phil_LNP_modelling">https://github.com/pharmbio/phil_LNP_modelling</a><br></div><div><br></div><div><br></div><div><br></div><div><br></div><div><br></div><p></p>…”

MCCN Case Study 1 - Evaluate impact from environmental events/pressures by Donald Hobern (21435904)

“…filters=eyJTVEFURSI6WyJBQ1QiXX0=&location=-35.437128,149.203518,11.00</a></li><li><b>caladenia_act.csv</b> - Distribution records for orchids in the genus <i>Caladenia</i> between 1990 and present from the ALA in CSV format: <a href="https://doi.org/10.26197/ala.1e501311-7077-403b-a743-59e096068fa0" target="_blank">https://doi.org/10.26197/ala.1e501311-7077-403b-a743-59e096068fa0</a></li></ul><h4><b>Dependencies</b></h4><ul><li>This notebook requires Python 3.10 or higher</li><li>Install relevant Python libraries with: <b>pip install mccn-engine rocrate</b></li><li>Installing mccn-engine will install other dependencies</li></ul><h4><b>Overview</b></h4><ol><li>Group orchid species records by species</li><li>Prepare STAC metadata records for each data source (separate records for the distribution data for each orchid species)</li><li>Load data cube</li><li>Mask orchid distribution records to boundaries of ACT</li><li>Calculate the proportion of distribution records for each species occurring inside and outside protected areas</li><li>Calculate the proportion of distribution records for each species occurring in areas with each class of vegetation cover</li><li>Report the apparent affinity between each species and protected areas and between each species and different classes of vegetation cover</li></ol><h4><b>Notes</b></h4><ul><li>No attempt is made here to compensate for underlying bias in the areas where observers have spent time recording orchids. …”

Western Oregon Wet Dry (WOWTDR) annual predictions of late summer streamflow status for western Oregon, 2019-2021 by Jonathan D. Burnett (19659601)

“…Also included is all R code and Python code needed to run and process this model.…”

Neural-Signal Tokenization and Real-Time Contextual Foundation Modelling for Sovereign-Scale AGI Systems by Lakshit Mathur (20894549)

Measurement data from full-scale fire experiments of battery electric vehicles and internal combustion engine vehicles by Nathaniel G. Sauer (22463233)

“…</li><li><strong>data_heatflux.zip</strong>: ZIP archive containing 12 HDF5 files (readable via Python <code>h5py</code>). Six files (<code>T_XX</code>) record temperature and six (<code>HF_XX</code>) record incident radiative heat flux to plate sensors located along the driver and passenger sides of the vehicle. …”

Cognitive Fatigue by Rui Varandas (11900993)

“…<br></p><p dir="ltr"><b>HCI features</b> encompass keyboard, mouse, and screenshot data. Below is a Python code snippet for extracting screenshot files from the screenshots CSV file.…”

Endothelial cells stably infected with recombinant Kaposi’s sarcoma-associated herpesvirus display distinct viscoelastic and morphological properties by Majahonkhe Shabangu (17340538)

“…<p dir="ltr">Data and code supporting work presented in article.</p><p dir="ltr">File: 01_preprocessing_macro.ijm</p><p dir="ltr">Description: A simplified macro outlining time-lapse image pre-processing prior to mitochondria-tracking analysis in TrackMate (Image J). …”

Data by Yasir Çatal (20329092)

“…Flexibility of Intrinsic Neural Timescales During Distinct Behavioral States<h2>Description of the data and file structure</h2><p dir="ltr">The github page <a href="https://github.com/duodenum96/acw_behavior" target="_blank">https://github.com/duodenum96/acwbehavior</a> contains the MATLAB code to replicate the figures. The numerical data necessary for the figures are presented here. …”

Learning States by Rui Varandas (11900993)

“…<br></p><p dir="ltr"><b>HCI features</b> encompass keyboard, mouse, and screenshot data. Below is a Python code snippet for extracting screenshot files from the screenshots CSV file.​…”

<b>InterHub: A Naturalistic Trajectory Dataset with Dense Interaction for Autonomous Driving</b> by Xiyan Jiang (20320758)

“…</b></li></ul><p dir="ltr">The Python codes used to process and analyze the dataset can be found at <a href="https://github.com/zxc-tju/InterHub" rel="noreferrer" target="_blank">https://github.com/zxc-tju/InterHub</a>. …”

Horuss Research: methodology for validating unstructured data using large language models by Fabiano Castello (6803171)

Replication Package: "The SBOM Gap: Adoption and Compliance in Open Source Software" by anonymous author (14191683)

“…<p dir="ltr">Replication Package Structure:</p><p dir="ltr">The replication package contains all data and scripts necessary to reproduce the analyses and results presented in this study.</p><p><br></p><p dir="ltr">replication_package/</p><p>│</p><p dir="ltr">├── data/</p><p dir="ltr">│ ├── sbom_repo_paths.csv # Repository paths and metadata for analyzed projects</p><p dir="ltr">│ ├── sbom_project_features.csv # Extracted features for SBOM projects</p><p dir="ltr">│ ├── non_sbom_project_features.csv # Extracted features for non-SBOM projects</p><p dir="ltr">│ └── SBOM_files/ # Raw SBOM files collected from selected repositories</p><p>│</p><p dir="ltr">└── code/</p><p dir="ltr"> ├── RQ1_regression/ # Scripts for regression analysis (RQ1)</p><p dir="ltr"> │ ├── regression.R # Main regression analysis script</p><p dir="ltr"> │ └── common.R # Shared functions for data filtering and formatting</p><p> │</p><p dir="ltr"> └── RQ2_compliance/ # Scripts for compliance and coverage checks (RQ2)</p><p dir="ltr"> ├── check_component_name.py</p><p dir="ltr"> ├── check_component_version.py</p><p dir="ltr"> ├── check_supplier.py</p><p dir="ltr"> ├── check_unique_identifiers.py</p><p dir="ltr"> ├── check_sbom_author.py</p><p dir="ltr"> ├── check_timestamp.py</p><p dir="ltr"> ├── check_dependency.py</p><p dir="ltr"> ├── check_hash.py</p><p dir="ltr"> ├── check_lifecycle_phase.py</p><p dir="ltr"> ├── check_license.py</p><p dir="ltr"> ├── check_vex.py</p><p dir="ltr"> ├── check_transitive_dependency.py</p><p dir="ltr"> ├── check_circular_dep.py</p><p dir="ltr"> └── check_all_7_min_req_files.py</p><p dir="ltr"><br></p><p dir="ltr"><br></p><p><br></p><p dir="ltr">Folder Descriptions:</p><p><br></p><p dir="ltr">data/: Contains datasets and raw SBOM files used in the analysis.…”

Automated Discovery of Semantic Attacks in Multi-Robot Navigation Systems - Research Artifacts by Doguhan Yeke (21498410)

“…<h4>We present the research artifacts for our USENIX Security 2025 submission. …”