Quantitative Structure-Use Relationship Model thresholds for Model Validation, Domain of Applicability, and Candidate Alternative Selection

This file contains value of the model training set confusion matrix, domain of applicability evaluation based on training set to predicted chemicals structural similarity, and 75th percentile bioactivity index values for each QSUR model.

This dataset is associated with the following publication: Phillips, K., J. Wambaugh, C. Grulke, K. Dionisio, and K. Isaacs. High-throughput screening of chemicals as functional substitutes using structure-based classification models. GREEN CHEMISTRY. Royal Society of Chemistry, Cambridge, UK, 19: 1063-1074, (2017).

Data and Resources

Field Value
accessLevel public
bureauCode {020:00}
catalog_conformsTo https://project-open-data.cio.gov/v1.1/schema
identifier A-wdcg-509
license https://pasteur.epa.gov/license/sciencehub-license.html
modified 2016-11-30
programCode {020:095}
publisher U.S. EPA Office of Research and Development (ORD)
publisher_hierarchy U.S. Government > U.S. Environmental Protection Agency > U.S. EPA Office of Research and Development (ORD)
references {https://doi.org/10.1039/c6gc02744j}
resource-type Dataset
source_datajson_identifier true
source_hash ef943cb8628371f732f1509207a08c0129cd0627
source_schema_version 1.1
Groups
  • AmeriGEOSS
  • National Provider
  • North America
Tags
  • AmeriGEO
  • AmeriGEOSS
  • CKAN
  • GEO
  • GEOSS
  • National
  • North America
  • United States
  • alternatives-assement
  • consumer-products
  • expocast
  • functional-use
  • high-throughput-screening
  • machine-learning-algorithms
  • qsar
isopen False
license_id other-license-specified
license_title other-license-specified
maintainer Katherine Phillips
maintainer_email phillips.katherine@epa.gov
metadata_created 2025-09-24T05:43:26.207871
metadata_modified 2025-09-24T05:43:26.207879
notes This file contains value of the model training set confusion matrix, domain of applicability evaluation based on training set to predicted chemicals structural similarity, and 75th percentile bioactivity index values for each QSUR model. This dataset is associated with the following publication: Phillips, K., J. Wambaugh, C. Grulke, K. Dionisio, and K. Isaacs. High-throughput screening of chemicals as functional substitutes using structure-based classification models. GREEN CHEMISTRY. Royal Society of Chemistry, Cambridge, UK, 19: 1063-1074, (2017).
num_resources 1
num_tags 15
title Quantitative Structure-Use Relationship Model thresholds for Model Validation, Domain of Applicability, and Candidate Alternative Selection