Comparison data 2 for <i>Lamprologus ocellatus</i>. by Nicolai Kraus (19949667)

“…TIBA accepts data outputs from popular logging software and is implemented in Python and JavaScript, with all current browsers supported. …”

Comparison data 5 for <i>Lamprologus ocellatus</i>. by Nicolai Kraus (19949667)

“…TIBA accepts data outputs from popular logging software and is implemented in Python and JavaScript, with all current browsers supported. …”

Comparison data 6 for <i>Lamprologus ocellatus</i>. by Nicolai Kraus (19949667)

“…TIBA accepts data outputs from popular logging software and is implemented in Python and JavaScript, with all current browsers supported. …”

Dataset for the Modeling and Bibliometric Analysis of Business plan for Entrepreneurship by Shofie Galuh Amanda (22121604)

“…The analysis and visualization were carried out using R Biblioshiny for thematic mapping and trend topics, and Microsoft Excel for main information and annual publication production. For modeling, Python was applied to generate projection analyses of annual scientific production using polynomial regression. …”

Iterative Methods for Vecchia-Laplace Approximations for Latent Gaussian Process Models by Pascal Kündig (19824557)

“…<p>Latent Gaussian process (GP) models are flexible probabilistic nonparametric function models. …”

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

Leveraging Large Language Models as Requirements Elicitation Interview Bots-all data by Samuel Gorsch (19947618)

“…<p dir="ltr"><b>Title:</b> Code and Supplementary Files for "Leveraging Large Language Models as Requirements Elicitation Interview Bots"</p><p dir="ltr"><b>Description:</b><br>This repository contains all code, supplementary plots, and select data files used in the master’s thesis, "Leveraging Large Language Models (LLMs) as Requirements Elicitation Interview Bots." …”

Examples of beekeeper associations resulting from using pollen images. by Juan D. Leal Campuzano (22470316)

Flowchart of the geographic origin classification process. by Juan D. Leal Campuzano (22470316)

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

“…</p><p dir="ltr"><b>Availability</b> — The repository includes LaTeX sources, trained model checkpoints, Python/PyTorch code, and synthetic datasets. Data are released under a Creative Commons Attribution-NonCommercial-4.0 (CC BY-NC 4.0) license; code under MIT License.…”

Code for the HIVE Appendicitis prediction modelRepository with LLM_data_extractor_optuna for automated feature extraction by Anoeska Schipper (18513465)

“…<p dir="ltr">This repository contains the code and trained model for developing the HIVE (History, Intake, Vitals, Examination) machine learning model for predicting appendicitis in patients presenting with acute abdominal pain at the Emergency Department (ED).…”

<b>Beyond absolute space: Modeling disease dispersion and reactive actions from a multi-spatialization perspective</b> by Shiran Zhong (14518376)

“…The following sections will guide you through the setup, data structure, code execution, expected output, and any additional notes necessary for reproducing the results presented in the manuscript.</p><p dir="ltr"><b>Table of Contents</b></p><p dir="ltr">· Requirements</p><p dir="ltr">· Data files</p><p dir="ltr">· Code structure</p><p dir="ltr">· Running the code</p><p dir="ltr">· Expected Output</p><p dir="ltr">· Troubleshooting</p><h3>==========================================================</h3><h3>Requirements</h3><p dir="ltr"><u>Operating system</u></p><p dir="ltr">· Windows 7 or higher (recommended)</p><p dir="ltr">· Ubuntu</p><p dir="ltr"><u>Software</u></p><p dir="ltr">· Python (version 2.7 or higher) or Jupyter Notebook</p><p dir="ltr">Required libraries: numpy, pandas, scipy, matplotlib, pgmpy</p><h3>Data files</h3><ul><li>Survey_data_processed_Anonymized.csv</li><li>ProtectiveAction_Anonymized.csv</li></ul><p dir="ltr">These two data files have been pre-processed from the raw survey data to support the Python code for generating Figures 3, 4, 5, and 6. …”

DataSheet1_Prostruc: an open-source tool for 3D structure prediction using homology modeling.PDF by Shivani V. Pawar (20355171)

“…However, existing tools often require significant expertise and computational resources, presenting a barrier for many researchers.</p>Methods<p>Prostruc is a Python-based homology modeling tool designed to simplify protein structure prediction through an intuitive, automated pipeline. …”

DataSheet1_Prostruc: an open-source tool for 3D structure prediction using homology modeling.PDF by Shivani V. Pawar (20355171)

“…However, existing tools often require significant expertise and computational resources, presenting a barrier for many researchers.</p>Methods<p>Prostruc is a Python-based homology modeling tool designed to simplify protein structure prediction through an intuitive, automated pipeline. …”

Table 1_Net2Brain: a toolbox to compare artificial vision models with human brain responses.pdf by Domenic Bersch (21248975)

“…To address these challenges, we present Net2Brain, a Python-based toolbox that provides an end-to-end pipeline for incorporating DNNs into neuroscience research, encompassing dataset download, a large selection of models, feature extraction, evaluation, and visualization. …”

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

“…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. …”

Data Sheet 1_Research on propagation dynamics of emotional contagion using S3EIR model based on multiple social media platforms.pdf by Hejie Chen (3947525)

“…In order to verify the validity and applicability of the S3EIR model, this paper constructs a dynamical model.</p>Methods<p>It uses Python to crawl the comments of the family-seeking event on the four social platforms and uses simulation to simulate and verify the dynamic process of emotional contagion and information dissemination.…”

Supplementary file 1_ParaDeep: sequence-based deep learning for residue-level paratope prediction using chain-aware BiLSTM-CNN models.docx by Piyachat Udomwong (22563212)

“…The implementation is freely available at https://github.com/PiyachatU/ParaDeep, with Python (PyTorch) code and a Google Colab interface for ease of use.…”

ML model for prediction of postpartum rehospitalization in pregnant women/new mothers using readily obtainable pre-pregnancy or early pregnancy sociodemographic and health determin... by Martin Frasch (5754731)

“…</li><li>Here, we present an open-access Python code including the ML model for inference to facilitate prospective utilization of the developed model and further study of the nuMoM2b and similar datasets with machine learning approaches.…”

Dataset of experimental and computational characterization of tissue spheroid fusion by Steven Ongenae (19646189)

“…Various csv and xlsx files are attached, which can be readily imported using pandas in Python, relating to: - processed experimental fusion data (100 cells, 500 cells, and new JASP experiments) - measures of granularity / contact angles using GSI - MSRD data from two-photon microscopy experiments - Combined data of all parameter studies and their extracted metrics from the computational model. …”