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# Model documentation & parameters
## Parameters
### Model
Whether to use the model trained 1) on procedures for heterogeneous single-atom catalyst synthesis, or 2) on organic chemistry procedures.
### Synthesis text
Synthesis procedure (in English prose) to extract actions from.
# Model card -- Text mining synthesis protocols of heterogeneous single-atom catalysts
**Model Details**:
Sequence-to-sequence transformer model
**Developers**:
Manu Suvarna, Alain C. Vaucher, Sharon Mitchell, Teodoro Laino, and Javier Pérez-Ramírez.
**Distributors**:
Same as the *developers*.
**Model date**:
April 2023.
**Algorithm version**:
Details in the source code and in the paper.
**Model type**:
A Transformer-based sequence-to-sequence language model that extracts synthesis actions from procedure text.
The model relies on the [OpenNMT](https://github.com/OpenNMT/OpenNMT-py) library.
**Information about training algorithms, parameters, fairness constraints or other applied approaches, and features**:
Details in the source code and in the paper.
**Paper or other resource for more information**:
Currently under review.
**License**: MIT
**Where to send questions or comments about the model**:
Contact one of the *developers*.
**Intended Use. Use cases that were envisioned during development**:
Chemical research, in particular in the field of heterogeneous single-atom catalysts.
**Primary intended uses/users**:
Researchers and computational chemists using the model for model comparison or research exploration purposes.
**Out-of-scope use cases**:
Production-level inference.
**Factors**:
Not applicable.
**Metrics**:
Details in the source code and in the paper.
**Datasets**:
Details in the source code and in the paper.
**Ethical Considerations**:
No specific considerations as no private/personal data is involved.
Please consult with the authors in case of questions.
**Caveats and Recommendations**:
Please consult with original authors in case of questions.
Model card prototype inspired by [Mitchell et al. (2019)](https://dl.acm.org/doi/abs/10.1145/3287560.3287596).
## Citation
```bib
@article{suvarna2023textmining,
title={Text mining and standardization of single-atom catalyst protocols to foster digital synthesis},
author={Manu Suvarna, Alain C. Vaucher, Sharon Mitchell, Teodoro Laino, and Javier Pérez-Ramírez},
journal={under review},
}
```
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