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__pycache__
__pycache__
 
 
csvs_for_training
csvs_for_training
 
 
data
data
 
 
utils
utils
 
 
.gitignore
.gitignore
 
 
README.md
README.md
 
 
abstract_prep.py
abstract_prep.py
 
 
abstracts.py
abstracts.py
 
 
cache_predictions_ensemble.sh
cache_predictions_ensemble.sh
 
 
combine_prediction_files.py
combine_prediction_files.py
 
 
covidence_data_aug.py
covidence_data_aug.py
 
 
download_csvs_from_covidence.py
download_csvs_from_covidence.py
 
 
highlight_utils.py
highlight_utils.py
 
 
inclusion_prediction.py
inclusion_prediction.py
 
 
long_sequence_tools.py
long_sequence_tools.py
 
 
make_pio_predictions.py
make_pio_predictions.py
 
 
post_predictions.py
post_predictions.py
 
 
prepare_text_for_prediction.py
prepare_text_for_prediction.py
 
 
run_opot.py
run_opot.py
 
 
sts_tools.py
sts_tools.py
 
 
train_classifiers.sh
train_classifiers.sh
 
 

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To train, run train_models.sh
To run the OPOT script and upload predictions, run cache_predictions_ensemble.sh. You will need to train the models first
You must have the fields "COVIDENCE_REVIEW_ID", "USERNAME", "PASSWORD", and "SERVER_IP" in a .env file, corresponding to the covidence review ID, the covidence username and password, and the server IP of the predictions server, respectively.

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