Notice: The reproducibility variables underlying each score are classified using an automated LLM-based pipeline, validated against a manually labeled dataset. LLM-based classification introduces uncertainty and potential bias; scores should be interpreted as estimates. Full accuracy metrics and methodology are described in Coakley et alK. L. Coakley, T. Snelleman, H. Hoos, and O. E. Gundersen, "The embrace of open science: An analysis of a decade of AI research and 56 800 conference papers," Under Review, 2026..
Stable Feature Selection from Brain sMRI
Authors: Bo Xin, Lingjing Hu, Yizhou Wang, Wen Gao
AAAI 2015 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Experiments show that the proposed nonnegative model performs much better in exploring the intrinsic structure of data via selecting stable features compared with other state-of-the-arts. |
| Researcher Affiliation | Academia | National Engineering Laboratory for Video Technology, Key Laboratory of Machine Perception, School of EECS, Peking University, Beijing, 100871, China Yanjing Medical College, Capital Medical University, Beijing, 101300, China |
| Pseudocode | No | The paper describes algorithms and mathematical formulations but does not include structured pseudocode or an algorithm block. |
| Open Source Code | No | No explicit statement or link providing access to the open-source code for the described methodology was found. |
| Open Datasets | Yes | The data are obtained from the Alzheimer s Disease Neuroimaging Initiative (ADNI) database2. We split all the baseline data into 1.5T and 3.0T MRI scans datasets (named 15T and 30T). 2http://adni.loni.ucla.edu |
| Dataset Splits | Yes | 10-fold cross-validation (CV) evaluation is applied and the classification accuracy for all tasks are summarized in Tab. 2. |
| Hardware Specification | Yes | All experiments are carried out on an Intel(R) Core(TM) i7-3770 CPU at 3.40GHz. |
| Software Dependencies | Yes | Although off-the-shelf convex solvers such as CVX (Grant and Boyd 2013) can be applied to solve the optimization, it hardly scales to high-dimensional problems in feasible time. |
| Experiment Setup | No | For each model, we used grid-search to find the optimal parameters respectively. No specific hyperparameters, ranges for grid search, or resulting optimal parameters are provided for reproducibility. |