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

S1 Data - by Haoqiang Liu (193675)

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)

Synthetic Realness: Authenticity Collapse in the Age of AI by Reality Drift Working Papers Series 2020-2025 (22445446)

Bayesian Spatial Binary Regression for Label Fusion in Structural Neuroimaging by D. Andrew Brown (6584837)

UK Biobank data wrangling statistics and results. by Simeone Marino (81051)

Supplementary Material for: Penalized Logistic Regression Analysis for Genetic Association Studies of Binary Phenotypes by Yu Y. (3096192)

“…We consider two approximate approaches to maximizing the marginal likelihood: (i) a Monte Carlo EM algorithm (MCEM) and (ii) a Laplace approximation (LA) to each integral, followed by derivative-free optimization of the approximation. …”

The data processing and analysis pipeline. by Xin Zhang (35492)

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). …”

SHAP bar plot. by Meng Cao (105914)

“…According to the SHAP analysis of the optimal model, the most influential predictors are age, education level, and hemoglobin concentration.…”

Sample screening flowchart. by Meng Cao (105914)

“…According to the SHAP analysis of the optimal model, the most influential predictors are age, education level, and hemoglobin concentration.…”

Descriptive statistics for variables. by Meng Cao (105914)

“…According to the SHAP analysis of the optimal model, the most influential predictors are age, education level, and hemoglobin concentration.…”

SHAP summary plot. by Meng Cao (105914)

“…According to the SHAP analysis of the optimal model, the most influential predictors are age, education level, and hemoglobin concentration.…”

ROC curves for the test set of four models. by Meng Cao (105914)

“…According to the SHAP analysis of the optimal model, the most influential predictors are age, education level, and hemoglobin concentration.…”

Display of the web prediction interface. by Meng Cao (105914)

“…According to the SHAP analysis of the optimal model, the most influential predictors are age, education level, and hemoglobin concentration.…”

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

Data_Sheet_1_A real-time driver fatigue identification method based on GA-GRNN.ZIP by Xiaoyuan Wang (492534)

tUbenet Foundation Model Weights by Natalie Holroyd (7099391)