{"model":"DIO3_inhibition","predicts":"Type 3 iodothyronine deiodinase (DIO3) inhibition","confidence":0.8,"output":"A conformal prediction region per compound: active, inactive, both (undecided at this confidence) or empty (outside the applicability domain), with the p-values p_inactive and p_active. Not a probability.","max_compounds_per_request":2000,"usage":{"GET /predict?smiles=<SMILES>":"one compound; repeat smiles= or comma-separate for more","POST /predict (application/json)":"{\"smiles\": \"<SMILES>\"} or {\"smiles\": [\"<SMILES>\", ...]}","POST /predict (multipart/form-data)":"a CSV or TSV file in the field \"file\", with a column whose name contains \"smiles\"","POST /predict (text/csv or text/tab-separated-values)":"the same table as the request body","?format=csv":"return a CSV instead of JSON","/docs":"interactive API documentation"},"citation":"Dracheva, E.; Norinder, U.; Rydén, P.; Engelhardt, J.; Weiss, J. M.; Andersson, P. L. In Silico Identification of Potential Thyroid Hormone System Disruptors among Chemicals in Human Serum and Chemicals with a High Exposure Index. Environ. Sci. Technol. 2022. doi:10.1021/acs.est.1c07762"}