Processed Dataset for “Modeling and Optimization of a Mixed-Model Two-Sided Assembly Line Balancing Problem Considering a Workstation-Sharing Mechanism” by Lingling Hu (22555691)

“…</p><p dir="ltr">The data are provided in <code>.xlsx</code> format and may be freely accessed and reused for <b>academic and non-commercial purposes only</b>.…”

Text-to-SQL Verification Methods and Benchmark by Tarfah Alrashed (15442229)

“…The code allows for the reproduction of our verification experiments and the evaluation of other verification algorithms on our new benchmark.…”

Classification of cell types in the leaf and the sepal. by Frances K. Clark (5617169)

“…Associated with <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.3003469#pbio.3003469.s010" target="_blank">S10 Fig</a>. The code and data associated with this figure can be found at Open Science Framework (osf.io), <a href="https://doi.org/10.17605/OSF.IO/RFCWS" target="_blank">https://doi.org/10.17605/OSF.IO/RFCWS</a>.…”

Multi-Task Learning for Gaussian Graphical Regressions with High Dimensional Covariates by Jingfei Zhang (580874)

“…We also develop an efficient augmented Lagrangian algorithm for computation, which solves subproblems with a semi-smooth Newton method. …”

The 2009 FDA PRO guidance, Potential Type I error, Descriptive Statistics and Pragmatic estimation of the number of interviews for item elicitation by Josh Fleckner (22075124)

“…The URN model provides a framework to demonstrate that an algorithm such as “first interview with zero new codes” may establish that all codes have been elicited. …”

Gaze Inputs for Targeting: The Eyes Have It, Not With a Cursor by Ajoy S. Fernandes (22293773)

“…If the participant looked out of the grid boundary, on button press, we chose to select the last targeted element, but no other algorithms to enhance performance were employed. …”

TreeMap 2016: A tree-level model of the forests of the conterminous United States circa 2016 by Karin L. Riley (19657882)

“…We used a random forests machine-learning algorithm to impute the forest plot data to a set of target rasters provided by Landscape Fire and Resource Management Planning Tools (LANDFIRE: https://landfire.gov). …”

ImproBR Replication Package by Anonymus (18533633)

“…<br><br>**Import Errors:**<br>Make sure you're in the replication package directory:<br>```bash<br>cd ImproBR-Replication<br>python improbr_pipeline.py --help<br>```<br><br>## Research Results & Evaluation Data<br>### RQ1: Bug Report Improvement Evaluation (139 reports)<br>**Manual Evaluation Results:**<br>- [`RQ1-RQ2/RQ1/manual_evaluation/Author 1 Responses.csv`](<u>RQ1-RQ2/RQ1/manual_evaluation/Author 1 Responses.csv</u>) - First evaluator assessments<br>- [`RQ1-RQ2/RQ1/manual_evaluation/Author 2 Responses.csv`](<u>RQ1-RQ2/RQ1/manual_evaluation/Author 2 Responses.csv</u>) - Second evaluator assessments <br>- [`RQ1-RQ2/RQ1/manual_evaluation/Final Results.csv`](<u>RQ1-RQ2/RQ1/manual_evaluation/Final Results.csv</u>) - Consolidated evaluation results<br><br>**Inter-Rater Agreement (Cohen's Kappa):**<br>- [`RQ1-RQ2/RQ1/cohen's_cappa_coefficient_matrices/confusion_matrix_s2r_label.png`](<u>RQ1-RQ2/RQ1/cohen's_cappa_coefficient_matrices/confusion_matrix_s2r_label.png</u>) - Steps to Reproduce κ scores<br>- [`RQ1-RQ2/RQ1/cohen's_cappa_coefficient_matrices/confusion_matrix_ob_label.png`](<u>RQ1-RQ2/RQ1/cohen's_cappa_coefficient_matrices/confusion_matrix_ob_label.png</u>) - Observed Behavior κ scores<br>- [`RQ1-RQ2/RQ1/cohen's_cappa_coefficient_matrices/confusion_matrix_eb_label.png`](<u>RQ1-RQ2/RQ1/cohen's_cappa_coefficient_matrices/confusion_matrix_eb_label.png</u>) - Expected Behavior κ scores<br><br>**Algorithm Results:**<br>- [`RQ1-RQ2/RQ1/algorithm_results/improbr_outputs/`](<u>RQ1-RQ2/RQ1/algorithm_results/improbr_outputs/</u>) - ImproBR improved reports<br>- [`RQ1-RQ2/RQ1/algorithm_results/chatbr_outputs/`](<u>RQ1-RQ2/RQ1/algorithm_results/chatbr_outputs/</u>) - ChatBR baseline results<br>- [`RQ1-RQ2/RQ1/algorithm_results/bee_analysis/`](<u>RQ1-RQ2/RQ1/algorithm_results/bee_analysis/</u>) - BEE tool structural analysis<br><br>### RQ2: Comparative Analysis vs ChatBR (37 pairs)<br>**Similarity Score Results:**<br>- [`RQ1-RQ2/RQ2/algorithm_results/similarity_scores/overall_tfidf.csv`](<u>RQ1-RQ2/RQ2/algorithm_results/similarity_scores/overall_tfidf.csv</u>) - TF-IDF similarity scores<br>- [`RQ1-RQ2/RQ2/algorithm_results/similarity_scores/overall_word2vec.csv`](<u>RQ1-RQ2/RQ2/algorithm_results/similarity_scores/overall_word2vec.csv</u>) - Word2Vec similarity scores<br>- [`RQ1-RQ2/RQ2/algorithm_results/similarity_scores/exact_string_comparisons.json`](<u>RQ1-RQ2/RQ2/algorithm_results/similarity_scores/exact_string_comparisons.json</u>) - Complete TF-IDF comparison with scores for each comparison unit (full debugging)<br>- [`RQ1-RQ2/RQ2/algorithm_results/similarity_scores/word2vec_comparisons.json`](<u>RQ1-RQ2/RQ2/algorithm_results/similarity_scores/word2vec_comparisons.json</u>) - Complete Word2Vec comparison with scores for each comparison unit (full debugging)<br><br>**Algorithm Outputs:**<br>- [`RQ1-RQ2/RQ2/algorithm_results/ImproBR_outputs/`](<u>RQ1-RQ2/RQ2/algorithm_results/ImproBR_outputs/</u>) - ImproBR enhanced reports<br>- [`RQ1-RQ2/RQ2/algorithm_results/ChatBR_outputs/`](<u>RQ1-RQ2/RQ2/algorithm_results/ChatBR_outputs/</u>) - ChatBR baseline outputs<br>- [`RQ1-RQ2/RQ2/dataset/ground_truth/`](<u>RQ1-RQ2/RQ2/dataset/ground_truth/</u>) - High-quality reference reports<br>## Important Notes<br><br>1. …”

Data Sheet 1_Exploring nonlinear and interaction effects of urban campus built environments on exercise walking using crowdsourced data.csv by Bo Lu (241075)

“…</p>Methods<p>This study utilized crowdsourced exercise walking data and incorporated diverse campus characteristics to construct a multidimensional variable system. …”

Data Sheet 2_Exploring nonlinear and interaction effects of urban campus built environments on exercise walking using crowdsourced data.csv by Bo Lu (241075)

“…</p>Methods<p>This study utilized crowdsourced exercise walking data and incorporated diverse campus characteristics to construct a multidimensional variable system. …”

Genomic determinants in pathogenicity of SARS-CoV-2 versa common cold coronaviruses by Zahra Arab-Bafrani (20309630)

“…To this aim, at first, in the full genome of all coronavirus strains included in this study, the observed and expected frequency of dinucleotide to hexanucleotide was obtained using Markov method. Then odds ratio (observed/expected abundances) of short oligonucleotide was computed and considered as the raw data (features). …”

DataSheet1_Enhancing slope stability prediction through integrated PCA-SSA-SVM modeling: a case study of LongLian expressway.docx by Jianxin Huang (11944014)

“…Traditional slope stability analysis methods, such as the limit equilibrium method, limit analysis method, and finite element method, often face limitations due to computational complexity and the need for extensive soil property data. …”

Integrating drought warning water level with analytical hedging for reservoir water supply operation by Wenhua Wan (8051543)

“…</p><p dir="ltr">2. R codes for the HR-based DP algorithm, the processes deriving seasonal DWWL, and the statistical performance of HR with DWWL during typical drought years.…”

TreeMap 2020 CONUS: A tree-level model of the forests of the conterminous United States circa 2020 by Scott N. Zimmer (20807459)

“…We used a Random Forest machine-learning algorithm to impute the forest plot data to a set of target rasters provided by Landscape Fire and Resource Management Planning Tools (LANDFIRE) and Daymet (Daymet). …”

TreeMap 2022 CONUS: A tree-level model of the forests of the conterminous United States circa 2022 by Rachel M. Houtman (19658365)

“…We used a Random Forest machine-learning algorithm to impute the forest plot data to a set of target rasters provided by Landscape Fire and Resource Management Planning Tools (LANDFIRE) and Daymet (Daymet). …”

A Dataset on the Biodiversity Footprints and Sectoral Differences in China by haiyue wang (20803663)

“…It comprises the following components: (1) China’s raw species spatial data, sourced from the IUCN and BirdLife International, with 446 threatened and near-threatened species attributes provided in a CSV file. (2) Biodiversity footprint data of China's 19 economic sectors across 30 provinces (2017), with two versions: Version 1: 352 species (excluding NT species) Version 2: 446 species (including NT species) Stored as “2017 China Provincial Biodiversity Footprint Data” in Shapefile format. (3) Biodiversity footprint data by taxonomic group (Mammal, Amphibian, Reptile, and Bird) across 30 provinces (2017), with two versions as above, stored as “2017 China Taxonomic Biodiversity Footprint Data” in Shapefile format. (4) A procedural demonstration of matrix operations with detailed algorithmic steps for specific species, stored as “An example detailing the computational steps for specific species” in PDF format. (5) Code.…”

A Dataset on the Biodiversity Footprints and Sectoral Differences in China by Haiyue Wang (20698763)

“…<p dir="ltr">(1) China’s species data stored in the file “2017 China Species Spatial Data” in CSV format, spatial data sourced from the IUCN and BirdLife International.…”

Dataset for Partial Parallelism Plot Analysis in Neurodegeneration Biomarker Assays (2010–2024) by Axel Petzold (7076261)

“…<br></p><p dir="ltr">Each dataset entry is annotated with:</p><ul><li>Sample type (serum, plasma, cerebrospinal fluid)</li><li>Assay platform and dilution steps</li><li>Classification of outcome (partial parallelism achieved or not)</li></ul><p dir="ltr"><b>Use cases:</b><br>This dataset is designed to help researchers, assay developers, and meta-analysts to:</p><ul><li>Reproduce figures and analyses from the published review</li><li>Benchmark or validate new assay performance pipelines</li><li>Train algorithms for automated detection of dilutional non-parallelism</li></ul><p dir="ltr"><b>Files included:</b></p><ul><li><code>.csv</code> files containing dilution–response data</li><li>Metadata spreadsheets with assay and sample annotations</li></ul><p></p>…”

Both Ankle fNIRS MI dataset by Hammad Gilani (8060012)

“…</p><p dir="ltr">The dataset includes:</p><p><br></p><ul><li><b>Raw data:</b> Original <code>.nirs</code> files for each participant.…”

Right Knee fNIRS MI Dataset by Hammad Gilani (8060012)

“…</p><p dir="ltr">The dataset includes:</p><p><br></p><ul><li><b>Raw data:</b> Original <code>.nirs</code> files for each participant.…”