Upload state.json with huggingface_hub

state.json

@@ -1 +1 @@
-{"Brain_cancer_test": {"description": "Unknown case", "generative_models": {"data_path": "infrastructure/generative_models/autotrain/data/Brain_cancer_test/data.csv", "feature_column": ["canonical_smiles"], "target_column": null, "problem": null, "status": "Trained", "weights_path": "infrastructure/generative_models/autotrain/GAN_weights/train_GAN_Brain_cancer_test", "arch_type": null, "metric": null}, "ml_models": {"data_path": "automl\\data\\data_4j1r.csv", "feature_column": ["canonical_smiles"], "target_column": ["docking_score", "QED", "Synthetic Accessibility", "PAINS", "SureChEMBL", "Glaxo", "Brenk", "IC50"], "status": "Trained", "weights_path": {"regression": "infrastructure/automl/trained_data_Brain_cancer_test_regression", "classification": "infrastructure/automl/trained_data_Brain_cancer_test_classification"}, "metric": {"regression": {"rmse": 2.751}, "classification": {"roc_auc_pen": 0.836}}, "Predictable properties": {"regression": ["docking_score"], "classification": ["IC50"]}}}, "test_api": {"description": "Case for Brain canser", "generative_models": {"data_path": null, "feature_column": null, "target_column": null, "problem": null, "status": null, "weights_path": null, "arch_type": null, "metric": null}, "ml_models": {"data_path": "infrastructure/automl/data/test_api/data.csv", "feature_column": ["canonical_smiles"], "target_column": ["docking_score", "QED", "Synthetic Accessibility", "PAINS", "SureChEMBL", "Glaxo", "Brenk", "IC50"], "status": "Trained", "weights_path": {"regression": "infrastructure/automl/trained_data_test_api_regression", "classification": "infrastructure/automl/trained_data_test_api_classification"}, "metric": {"regression": {"rmse": 4.897}, "classification": {"roc_auc_pen": 0.857}}, "Predictable properties": {"regression": ["docking_score"], "classification": ["IC50"]}}}, "Alzheimer": {"description": "Case for Alzheimer with trained FEDOT pipelines for predict \"docking_score\", and \"IC50\"", "generative_models": {"data_path": "docked_data_for_train/data_4j1r.csv", "feature_column": null, "target_column": null, "problem": null, "status": "Trained", "weights_path": "autotrain/Alzheimer/weights", "arch_type": null, "metric": null}, "ml_models": {"data_path": "infrastructure/automl/data/Alzheimer/data.csv", "feature_column": ["canonical_smiles"], "target_column": ["docking_score", "QED", "Synthetic Accessibility", "PAINS", "SureChEMBL", "Glaxo", "Brenk", "IC50"], "status": "Trained", "weights_path": {"regression": "infrastructure/automl/train_model_data/trained_data_Alzheimer_regression", "classification": "infrastructure/automl/train_model_data/trained_data_Alzheimer_classification"}, "metric": {"regression": {"rmse": 1.029}, "classification": {"roc_auc_pen": 0.993}}, "Predictable properties": {"regression": ["docking_score"], "classification": ["IC50"]}}}, "MEK1": {"description": "", "generative_models": {"data_path": "/projects/generative_models_data/generative_models/transformer/autotrain/data/MEK1/data.csv", "feature_column": null, "target_column": null, "problem": null, "status": "Trained", "weights_path": "autotrain/train_MEK1/MEK1/weights", "arch_type": null, "metric": 10000}, "ml_models": {"data_path": "infrastructure/automl/data/MEK1/data.csv", "feature_column": ["smiles"], "target_column": ["IC50"], "status": "Trained", "weights_path": {"regression": "infrastructure/automl/train_model_data/trained_data_MEK1_regression", "classification": null}, "metric": {"regression": {"rmse": 9.223372036854776e+18}, "classification": null}, "Predictable properties": {"regression": ["IC50"]}}}, "___": {"description": "", "generative_models": {"data_path": null, "feature_column": null, "target_column": null, "problem": null, "status": null, "weights_path": null, "arch_type": null, "metric": null}, "ml_models": {"data_path": "infrastructure/automl/data/IC50_short/data.csv", "feature_column": ["canonical_smiles"], "target_column": ["IC50_"], "status": "Trained", "weights_path": {"regression": "infrastructure/automl/train_model_data/trained_data_IC50_short_regression", "classification": null}, "metric": {"regression": {"rmse": 3225.778}, "classification": null}, "Predictable properties": {"regression": ["IC50_"]}}}, "IC50_short": {"description": "", "generative_models": {"data_path": null, "feature_column": null, "target_column": null, "problem": null, "status": null, "weights_path": null, "arch_type": null, "metric": null}, "ml_models": {"data_path": "infrastructure/automl/data/IC50_short/data.csv", "feature_column": ["canonical_smiles"], "target_column": ["IC50"], "status": "Trained", "weights_path": {"regression": "infrastructure/automl/train_model_data/trained_data_IC50_short_regression", "classification": null}, "metric": {"regression": {"rmse": 9.223372036854776e+18}, "classification": null}, "Predictable properties": {"regression": ["canonical_smiles"]}}}, "IC50_v2": {"description": "", "generative_models": {"data_path": null, "feature_column": null, "target_column": null, "problem": null, "status": null, "weights_path": null, "arch_type": null, "metric": null}, "ml_models": {"data_path": "infrastructure/automl/data/IC50_v2/data.csv", "feature_column": ["canonical_smiles"], "target_column": ["IC50_"], "status": "Training", "weights_path": {"regression": "infrastructure/automl/train_model_data/trained_data_IC50_v2_regression", "classification": null}, "metric": null, "Predictable properties": {"regression": ["canonical_smiles"]}}}, "IC50_v3": {"description": "", "generative_models": {"data_path": null, "feature_column": null, "target_column": null, "problem": null, "status": "Trained", "weights_path": "autotrain/train_IC50_v3/IC50_v3/weights", "arch_type": null, "metric": 512.8530487697503}, "ml_models": {"data_path": "autotrain/data/IC50_v3/data.csv", "feature_column": ["canonical_smiles"], "target_column": ["IC50_"], "status": "Trained", "weights_path": {"regression": "infrastructure/automl/train_model_data/trained_data_IC50_v3_regression", "classification": null}, "metric": {"regression": {"rmse": 4367.945}, "classification": null}, "Predictable properties": {"regression": ["IC50_"]}}}, "IC50_v4": {"description": "", "generative_models": {"data_path": "autotrain/data/IC50_v4/data.csv", "feature_column": null, "target_column": null, "problem": null, "status": "Trained", "weights_path": "autotrain/train_IC50_v4/IC50_v4/weights", "arch_type": null, "metric": 3049.5868456197477}, "ml_models": {"data_path": "infrastructure/automl/data/IC50_v4/data.csv", "feature_column": ["canonical_smiles"], "target_column": ["IC50_"], "status": "Trained", "weights_path": {"regression": "infrastructure/automl/train_model_data/trained_data_IC50_v4_regression", "classification": null}, "metric": {"regression": {"rmse": 2898.559}, "classification": null}, "Predictable properties": {"regression": ["IC50_"]}}}, "kras_g12c_model": {"description": "", "generative_models": {"data_path": null, "feature_column": null, "target_column": null, "problem": null, "status": null, "weights_path": null, "arch_type": null, "metric": null}, "ml_models": {"data_path": "infrastructure/automl/data/kras_g12c_model/data.csv", "feature_column": ["smiles"], "target_column": ["IC50"], "status": "Training", "weights_path": {"regression": "infrastructure/automl/train_model_data/trained_data_kras_g12c_model_regression", "classification": null}, "metric": null, "Predictable properties": {"regression": ["smiles", "IC50"]}}}, "Alzheimer_1_prop": {"description": "Unknown case", "generative_models": {"data_path": null, "feature_column": null, "target_column": null, "problem": null, "status": "Training", "weights_path": "/projects/CoScientist/ChemCoScientist/generative_models/autotrain/train_Alzheimer_1_prop/Alzheimer_1_prop", "arch_type": null, "metric": 0.061100593427216965}, "ml_models": {"data_path": "automl\\data\\data_4j1r.csv", "feature_column": ["canonical_smiles"], "target_column": ["IC50"], "status": "Trained", "weights_path": {"regression": null, "classification": "infrastructure/automl/trained_data_Alzheimer_1_prop_classification"}, "metric": {"regression": null, "classification": {"roc_auc_pen": 0.934}}, "Predictable properties": {"classification": ["IC50"]}}}, "user_dataset": {"description": "", "generative_models": {"data_path": null, "feature_column": null, "target_column": null, "problem": null, "status": null, "weights_path": null, "arch_type": null, "metric": null}, "ml_models": {"data_path": "infrastructure/automl/data/user_dataset/data.csv", "feature_column": ["smiles"], "target_column": ["IC50"], "status": "Training", "weights_path": {"regression": "infrastructure/automl/train_model_data/trained_data_user_dataset_regression", "classification": null}, "metric": null, "Predictable properties": {"regression": ["IC50"]}}}, "gsk": {"description": "", "generative_models": {"data_path": null, "feature_column": null, "target_column": null, "problem": null, "status": null, "weights_path": null, "arch_type": null, "metric": null}, "ml_models": {"data_path": "infrastructure/automl/data/gsk/data.csv", "feature_column": ["smiles"], "target_column": ["IC50"], "status": "Trained", "weights_path": {"regression": "infrastructure/automl/train_model_data/trained_data_gsk_regression", "classification": null}, "metric": {"regression": {"rmse": 175251.993}, "classification": null}, "Predictable properties": {"regression": ["IC50"]}}}, "Alzheimer_regression": {"description": "Unknown case", "generative_models": {"data_path": null, "feature_column": null, "target_column": null, "problem": null, "status": null, "weights_path": null, "arch_type": null, "metric": null}, "ml_models": {"data_path": "automl\\data\\base_cases\\tau_kinase_inhib_reg.csv", "feature_column": ["Smiles"], "target_column": ["Standard Value"], "status": "Trained", "weights_path": {"regression": "infrastructure/automl/trained_data_Alzheimer_regression_regression", "classification": null}, "metric": {"regression": {"MAE score": 16337.023952957132, "MSE score": 2950887022.2051077, "R2 score": -5.34839103072603}, "classification": null}, "Predictable properties": {"regression": ["Standard Value"]}}}, "Alzheimer_regression_log": {"description": "Unknown case", "generative_models": {"data_path": null, "feature_column": null, "target_column": null, "problem": null, "status": null, "weights_path": null, "arch_type": null, "metric": null}, "ml_models": {"data_path": "D:\\Projects\\CoScientist\\automl\\data\\base_cases\\docked_all_kinase_inhib.csv", "feature_column": ["Smiles"], "target_column": ["Log Standard Value"], "status": "Trained", "weights_path": {"regression": "infrastructure/automl/trained_data_Alzheimer_regression_log_regression", "classification": null}, "metric": {"regression": {"MAE score": 1.284178704393584, "MSE score": 2.860851986095193, "R2 score": 0.6737074004236703}, "classification": null}, "Predictable properties": {"regression": ["Log Standard Value"]}}}, "Alzheimer_regression_Minimum_Energy_Rodion": {"description": "Unknown case", "generative_models": {"data_path": null, "feature_column": null, "target_column": null, "problem": null, "status": null, "weights_path": null, "arch_type": null, "metric": null}, "ml_models": {"data_path": "D:\\Projects\\CoScientist\\automl\\utils\\merged_result2_train.csv", "feature_column": ["canonical_smiles"], "target_column": ["Minimum Energy"], "status": "Trained", "weights_path": {"regression": "infrastructure/automl/trained_data_Alzheimer_regression_Minimum_Energy_Rodion_regression", "classification": null}, "metric": {"regression": {"MAE score": 2.9636140255192296, "MSE score": 54.5566406525315, "R2 score": 0.1196169881420317}, "classification": null}, "Predictable properties": {"regression": ["Minimum Energy"]}}}, "Alzheimer_regression_Minimum_Energy_Vitctor": {"description": "Unknown case", "generative_models": {"data_path": null, "feature_column": null, "target_column": null, "problem": null, "status": null, "weights_path": null, "arch_type": null, "metric": null}, "ml_models": {"data_path": "infrastructure\\automl\\IPPI\\4j1r_docking_train.csv", "feature_column": ["canonical_smiles"], "target_column": ["4j1r"], "status": "Training", "weights_path": {"regression": "infrastructure/automl/trained_data_Alzheimer_regression_Minimum_Energy_Vitctor_regression", "classification": null}, "metric": null, "Predictable properties": {"regression": ["4j1r"]}}}}
+{"Brain_cancer_test": {"description": "Unknown case", "generative_models": {"data_path": "infrastructure/generative_models/autotrain/data/Brain_cancer_test/data.csv", "feature_column": ["canonical_smiles"], "target_column": null, "problem": null, "status": "Trained", "weights_path": "infrastructure/generative_models/autotrain/GAN_weights/train_GAN_Brain_cancer_test", "arch_type": null, "metric": null}, "ml_models": {"data_path": "automl\\data\\data_4j1r.csv", "feature_column": ["canonical_smiles"], "target_column": ["docking_score", "QED", "Synthetic Accessibility", "PAINS", "SureChEMBL", "Glaxo", "Brenk", "IC50"], "status": "Trained", "weights_path": {"regression": "infrastructure/automl/trained_data_Brain_cancer_test_regression", "classification": "infrastructure/automl/trained_data_Brain_cancer_test_classification"}, "metric": {"regression": {"rmse": 2.751}, "classification": {"roc_auc_pen": 0.836}}, "Predictable properties": {"regression": ["docking_score"], "classification": ["IC50"]}}}, "test_api": {"description": "Case for Brain canser", "generative_models": {"data_path": null, "feature_column": null, "target_column": null, "problem": null, "status": null, "weights_path": null, "arch_type": null, "metric": null}, "ml_models": {"data_path": "infrastructure/automl/data/test_api/data.csv", "feature_column": ["canonical_smiles"], "target_column": ["docking_score", "QED", "Synthetic Accessibility", "PAINS", "SureChEMBL", "Glaxo", "Brenk", "IC50"], "status": "Trained", "weights_path": {"regression": "infrastructure/automl/trained_data_test_api_regression", "classification": "infrastructure/automl/trained_data_test_api_classification"}, "metric": {"regression": {"rmse": 4.897}, "classification": {"roc_auc_pen": 0.857}}, "Predictable properties": {"regression": ["docking_score"], "classification": ["IC50"]}}}, "Alzheimer": {"description": "Case for Alzheimer with trained FEDOT pipelines for predict \"docking_score\", and \"IC50\"", "generative_models": {"data_path": "docked_data_for_train/data_4j1r.csv", "feature_column": null, "target_column": null, "problem": null, "status": "Trained", "weights_path": "autotrain/Alzheimer/weights", "arch_type": null, "metric": null}, "ml_models": {"data_path": "infrastructure/automl/data/Alzheimer/data.csv", "feature_column": ["canonical_smiles"], "target_column": ["docking_score", "QED", "Synthetic Accessibility", "PAINS", "SureChEMBL", "Glaxo", "Brenk", "IC50"], "status": "Trained", "weights_path": {"regression": "infrastructure/automl/train_model_data/trained_data_Alzheimer_regression", "classification": "infrastructure/automl/train_model_data/trained_data_Alzheimer_classification"}, "metric": {"regression": {"rmse": 1.029}, "classification": {"roc_auc_pen": 0.993}}, "Predictable properties": {"regression": ["docking_score"], "classification": ["IC50"]}}}, "MEK1": {"description": "", "generative_models": {"data_path": "/projects/generative_models_data/generative_models/transformer/autotrain/data/MEK1/data.csv", "feature_column": null, "target_column": null, "problem": null, "status": "Trained", "weights_path": "autotrain/train_MEK1/MEK1/weights", "arch_type": null, "metric": 10000}, "ml_models": {"data_path": "infrastructure/automl/data/MEK1/data.csv", "feature_column": ["smiles"], "target_column": ["IC50"], "status": "Trained", "weights_path": {"regression": "infrastructure/automl/train_model_data/trained_data_MEK1_regression", "classification": null}, "metric": {"regression": {"rmse": 9.223372036854776e+18}, "classification": null}, "Predictable properties": {"regression": ["IC50"]}}}, "___": {"description": "", "generative_models": {"data_path": null, "feature_column": null, "target_column": null, "problem": null, "status": null, "weights_path": null, "arch_type": null, "metric": null}, "ml_models": {"data_path": "infrastructure/automl/data/IC50_short/data.csv", "feature_column": ["canonical_smiles"], "target_column": ["IC50_"], "status": "Trained", "weights_path": {"regression": "infrastructure/automl/train_model_data/trained_data_IC50_short_regression", "classification": null}, "metric": {"regression": {"rmse": 3225.778}, "classification": null}, "Predictable properties": {"regression": ["IC50_"]}}}, "IC50_short": {"description": "", "generative_models": {"data_path": null, "feature_column": null, "target_column": null, "problem": null, "status": null, "weights_path": null, "arch_type": null, "metric": null}, "ml_models": {"data_path": "infrastructure/automl/data/IC50_short/data.csv", "feature_column": ["canonical_smiles"], "target_column": ["IC50"], "status": "Trained", "weights_path": {"regression": "infrastructure/automl/train_model_data/trained_data_IC50_short_regression", "classification": null}, "metric": {"regression": {"rmse": 9.223372036854776e+18}, "classification": null}, "Predictable properties": {"regression": ["canonical_smiles"]}}}, "IC50_v2": {"description": "", "generative_models": {"data_path": null, "feature_column": null, "target_column": null, "problem": null, "status": null, "weights_path": null, "arch_type": null, "metric": null}, "ml_models": {"data_path": "infrastructure/automl/data/IC50_v2/data.csv", "feature_column": ["canonical_smiles"], "target_column": ["IC50_"], "status": "Training", "weights_path": {"regression": "infrastructure/automl/train_model_data/trained_data_IC50_v2_regression", "classification": null}, "metric": null, "Predictable properties": {"regression": ["canonical_smiles"]}}}, "IC50_v3": {"description": "", "generative_models": {"data_path": null, "feature_column": null, "target_column": null, "problem": null, "status": "Trained", "weights_path": "autotrain/train_IC50_v3/IC50_v3/weights", "arch_type": null, "metric": 512.8530487697503}, "ml_models": {"data_path": "autotrain/data/IC50_v3/data.csv", "feature_column": ["canonical_smiles"], "target_column": ["IC50_"], "status": "Trained", "weights_path": {"regression": "infrastructure/automl/train_model_data/trained_data_IC50_v3_regression", "classification": null}, "metric": {"regression": {"rmse": 4367.945}, "classification": null}, "Predictable properties": {"regression": ["IC50_"]}}}, "IC50_v4": {"description": "", "generative_models": {"data_path": "autotrain/data/IC50_v4/data.csv", "feature_column": null, "target_column": null, "problem": null, "status": "Trained", "weights_path": "autotrain/train_IC50_v4/IC50_v4/weights", "arch_type": null, "metric": 3049.5868456197477}, "ml_models": {"data_path": "infrastructure/automl/data/IC50_v4/data.csv", "feature_column": ["canonical_smiles"], "target_column": ["IC50_"], "status": "Trained", "weights_path": {"regression": "infrastructure/automl/train_model_data/trained_data_IC50_v4_regression", "classification": null}, "metric": {"regression": {"rmse": 2898.559}, "classification": null}, "Predictable properties": {"regression": ["IC50_"]}}}, "kras_g12c_model": {"description": "", "generative_models": {"data_path": null, "feature_column": null, "target_column": null, "problem": null, "status": null, "weights_path": null, "arch_type": null, "metric": null}, "ml_models": {"data_path": "infrastructure/automl/data/kras_g12c_model/data.csv", "feature_column": ["smiles"], "target_column": ["IC50"], "status": "Training", "weights_path": {"regression": "infrastructure/automl/train_model_data/trained_data_kras_g12c_model_regression", "classification": null}, "metric": null, "Predictable properties": {"regression": ["smiles", "IC50"]}}}, "Alzheimer_1_prop": {"description": "Unknown case", "generative_models": {"data_path": null, "feature_column": null, "target_column": null, "problem": null, "status": "Training", "weights_path": "/projects/CoScientist/ChemCoScientist/generative_models/autotrain/train_Alzheimer_1_prop/Alzheimer_1_prop", "arch_type": null, "metric": 0.061100593427216965}, "ml_models": {"data_path": "automl\\data\\data_4j1r.csv", "feature_column": ["canonical_smiles"], "target_column": ["IC50"], "status": "Trained", "weights_path": {"regression": null, "classification": "infrastructure/automl/trained_data_Alzheimer_1_prop_classification"}, "metric": {"regression": null, "classification": {"roc_auc_pen": 0.934}}, "Predictable properties": {"classification": ["IC50"]}}}, "user_dataset": {"description": "", "generative_models": {"data_path": null, "feature_column": null, "target_column": null, "problem": null, "status": null, "weights_path": null, "arch_type": null, "metric": null}, "ml_models": {"data_path": "infrastructure/automl/data/user_dataset/data.csv", "feature_column": ["smiles"], "target_column": ["IC50"], "status": "Training", "weights_path": {"regression": "infrastructure/automl/train_model_data/trained_data_user_dataset_regression", "classification": null}, "metric": null, "Predictable properties": {"regression": ["IC50"]}}}, "gsk": {"description": "", "generative_models": {"data_path": null, "feature_column": null, "target_column": null, "problem": null, "status": null, "weights_path": null, "arch_type": null, "metric": null}, "ml_models": {"data_path": "infrastructure/automl/data/gsk/data.csv", "feature_column": ["smiles"], "target_column": ["IC50"], "status": "Trained", "weights_path": {"regression": "infrastructure/automl/train_model_data/trained_data_gsk_regression", "classification": null}, "metric": {"regression": {"rmse": 175251.993}, "classification": null}, "Predictable properties": {"regression": ["IC50"]}}}, "Alzheimer_regression": {"description": "Unknown case", "generative_models": {"data_path": null, "feature_column": null, "target_column": null, "problem": null, "status": null, "weights_path": null, "arch_type": null, "metric": null}, "ml_models": {"data_path": "automl\\data\\base_cases\\tau_kinase_inhib_reg.csv", "feature_column": ["Smiles"], "target_column": ["Standard Value"], "status": "Trained", "weights_path": {"regression": "infrastructure/automl/trained_data_Alzheimer_regression_regression", "classification": null}, "metric": {"regression": {"MAE score": 16337.023952957132, "MSE score": 2950887022.2051077, "R2 score": -5.34839103072603}, "classification": null}, "Predictable properties": {"regression": ["Standard Value"]}}}, "Alzheimer_regression_log": {"description": "Unknown case", "generative_models": {"data_path": null, "feature_column": null, "target_column": null, "problem": null, "status": null, "weights_path": null, "arch_type": null, "metric": null}, "ml_models": {"data_path": "D:\\Projects\\CoScientist\\automl\\data\\base_cases\\docked_all_kinase_inhib.csv", "feature_column": ["Smiles"], "target_column": ["Log Standard Value"], "status": "Trained", "weights_path": {"regression": "infrastructure/automl/trained_data_Alzheimer_regression_log_regression", "classification": null}, "metric": {"regression": {"MAE score": 1.284178704393584, "MSE score": 2.860851986095193, "R2 score": 0.6737074004236703}, "classification": null}, "Predictable properties": {"regression": ["Log Standard Value"]}}}, "Alzheimer_regression_Minimum_Energy_Rodion": {"description": "Unknown case", "generative_models": {"data_path": null, "feature_column": null, "target_column": null, "problem": null, "status": null, "weights_path": null, "arch_type": null, "metric": null}, "ml_models": {"data_path": "D:\\Projects\\CoScientist\\automl\\utils\\merged_result2_train.csv", "feature_column": ["canonical_smiles"], "target_column": ["Minimum Energy"], "status": "Trained", "weights_path": {"regression": "infrastructure/automl/trained_data_Alzheimer_regression_Minimum_Energy_Rodion_regression", "classification": null}, "metric": {"regression": {"MAE score": 2.9636140255192296, "MSE score": 54.5566406525315, "R2 score": 0.1196169881420317}, "classification": null}, "Predictable properties": {"regression": ["Minimum Energy"]}}}, "Alzheimer_regression_Minimum_Energy_Vitctor": {"description": "Unknown case", "generative_models": {"data_path": null, "feature_column": null, "target_column": null, "problem": null, "status": null, "weights_path": null, "arch_type": null, "metric": null}, "ml_models": {"data_path": "infrastructure\\automl\\IPPI\\4j1r_docking_train.csv", "feature_column": ["canonical_smiles"], "target_column": ["4j1r"], "status": "Trained", "weights_path": {"regression": "infrastructure/automl/trained_data_Alzheimer_regression_Minimum_Energy_Vitctor_regression", "classification": null}, "metric": {"regression": {"MAE score": 0.4880074200685035, "MSE score": 0.4446727867220844, "R2 score": 0.7718743107322937}, "classification": null}, "Predictable properties": {"regression": ["4j1r"]}}}}