asreview-dory 1.2.3

ASReview New Exciting Models

ASReview Dory 🐟

ASReview Dory is an extension to the ASReview software, providing new models for classification and feature extraction. The extension is maintained by the ASReview LAB team.

How to cite
Please cite our Software Impacts paper (preferred) or the Zenodo software archive. See Citing this repository.

Installation

You can install ASReview Dory via PyPI using the following command:

pip install asreview-dory

⚠️ XGBoost on MacOS If you are using macOS and plan to use XGBoost, you should first install OpenMP (brew install libomp)

Model components

Feature Extractors:

Doc2Vec
GTR T5
LaBSE
MPNet
Multilingual E5
MXBAI
XLM RoBERTa

Classifiers:

AdaBoost
Neural Network - 2-Layer
Neural Network - Dynamic
Neural Network - Warm Start
XGBoost

Explore the performance of these models in our Simulation Gallery! Look for the 🐟 icon to spot the Dory models.

Usage

Once installed, the plugins will be available in the front-end of ASReview, as well as being accessible via the command-line interface.

You can check all available models using:

asreview algorithms

Caching Models

You can pre-load models to avoid downloading them during runtime by using the cache command. To cache specific models, such as xgboost and sbert, run:

asreview dory cache nb xgboost sbert

To cache all available models at once, use:

asreview dory cache-all

Exapmles

Documentation for adding your own custom models can be found in the docs folder here.

Examples of custom model integrations can be found in the examples folder here.

Compatibility

This plugin is compatible with ASReview version 2 or later. Ensure that your ASReview installation is up-to-date to avoid compatibility issues.

The development of this plugin is done in parallel with the development of the ASReview software. We aim to maintain compatibility with the latest version of ASReview, but please report any issues you encounter.

Citing this repository

If you use ASReview Dory in academic work, please cite our Software Impacts publication:

van der Kuil, T., Teijema, J. J., de Bruin, J., & van de Schoot, R. ASReview Dory: Bringing new and exciting models to ASReview LAB. Software Impacts, 27, 100809 (2026). https://doi.org/10.1016/j.simpa.2025.100809

If you are specifically citing the software itself (for example, to reference a particular version for reproducibility), please cite the Zenodo archived release: https://doi.org/10.5281/zenodo.15649247. The menu on the right can be used to find the citation format you need.

Contributing

We welcome contributions from the community. To contribute, please follow these steps:

1. Fork the repository.
2. Create a new branch for your feature or bug fix.
3. Implement your changes.
4. Commit your changes with a clear message.
5. Push your changes to your fork.
6. Open a pull request to the main repository.

Please ensure your code adheres to the existing style and includes relevant tests.

For any questions or further assistance, feel free to contact the ASReview Lab Developers.

---

Enjoy using ASReview Dory! We hope these new models enhance your systematic review processes.