S1 Data - by Haoqiang Liu (193675)

The Pseudo-Code of the IRBMO Algorithm. by Chenyi Zhu (9383370)

Pseudo Code of RBMO. by Chenyi Zhu (9383370)

Microsoft excel file containing exhaustive list of Abbreviated-Injury Scale codes used to generate binary variables encoding the presence or absence of injury to various body regio... by Michael D. Cobler-Lichter (22492930)

Surround Suppression mechanism. by Elnaz Nemati (21402730)

Variable Selection and Estimation for Misclassified Binary Responses and Multivariate Error-Prone Predictors by Li-Pang Chen (9747423)

“…<p>In statistical analysis or supervised learning, classification has been an attractive topic. Typically, a main goal is to adopt predictors to characterize the primarily interested binary random variables. …”

Classification and Regression Machine Learning Models for Predicting Aerobic Ready and Inherent Biodegradation of Organic Chemicals in Water by Kuan Huang (1504921)

“…This study addressed all these limitations by first compiling a large database of 12,750 records, considering both ready and inherent biodegradation under different conditions, and then developing regression and classification models using different chemical representations and ML algorithms. …”

Classification and Regression Machine Learning Models for Predicting Aerobic Ready and Inherent Biodegradation of Organic Chemicals in Water by Kuan Huang (1504921)

“…This study addressed all these limitations by first compiling a large database of 12,750 records, considering both ready and inherent biodegradation under different conditions, and then developing regression and classification models using different chemical representations and ML algorithms. …”

Classification and Regression Machine Learning Models for Predicting Aerobic Ready and Inherent Biodegradation of Organic Chemicals in Water by Kuan Huang (1504921)

“…This study addressed all these limitations by first compiling a large database of 12,750 records, considering both ready and inherent biodegradation under different conditions, and then developing regression and classification models using different chemical representations and ML algorithms. …”

Algoritmo de clasificación de expresiones de odio por tipos en español (Algorithm for classifying hate expressions by type in Spanish) by Daniel Pérez Palau (11097348)

“…</li></ul><p dir="ltr"><b>File Structure</b></p><p dir="ltr">The code generates and saves:</p><ul><li>Weights of the trained model (.h5)</li><li>Configured tokenizer</li><li>Training history in CSV</li><li>Requirements file</li></ul><p dir="ltr"><b>Important Notes</b></p><ul><li>The model excludes category 2 during training</li><li>Implements transfer learning from a pre-trained model for binary hate detection</li><li>Includes early stopping callbacks to prevent overfitting</li><li>Uses class weighting to handle category imbalances</li></ul><p dir="ltr">The process of creating this algorithm is explained in the technical report located at: Blanco-Valencia, X., De Gregorio-Vicente, O., Ruiz Iniesta, A., & Said-Hung, E. (2025). …”

Validation of image processing steps and metric results using images of a microfluidic device. by Gavrielle R. Untracht (11820311)

tUbenet Foundation Model Weights by Natalie Holroyd (7099391)

Fortran & C++: design fractal-type optical diffractive element by I-Lin Ho (13768960)

“…</p> <p>(4) export geometry/optics raw data and figures for binary DOE devices.</p> <p><br></p> <p>[Wolfram Mathematica code "square_triangle_DOE.nb"]:</p> <p>read the optimized binary DOE document (after Fortran & C++ code) to calculate its diffractive fields for comparison.…”

Predictive Analysis of Mushroom Toxicity Based Exclusively on Their Natural Habitat. by Enrico Bertozzi (22461709)

“…<br> <br>Conclusion<br><br>The study concludes that the habitat variable, used in isolation, is insufficient to create a safe and reliable mushroom toxicity classification model. The consistent accuracy of 70.28% does not represent a flaw in the SVM. algorithm, but rather the predictive performance ceiling of the feature itself, whose simplicity and class overlap limit the model's discriminatory ability. …”