Data and code for When does combined remediation add value? An estimand-based, hazard-aware evidence framework for Cu-contaminated soils
Description
This dataset contains the data, analysis files, and reproducible code supporting the systematic review and meta-analysis entitled “When does combined remediation add value? An estimand-based, hazard-aware evidence framework for Cu-contaminated soils”. The archive supports an estimand-based and hazard-aware evaluation of combined remediation strategies for Cu-contaminated soils. It distinguishes package activity (combined treatment versus untreated control), component-specific added value (combined treatment versus individual components), factorial interaction, and a conservative strongest-single-treatment benchmark. The deposited materials include the reconciled evidence map, study-level and arm-level quantitative data, effect-size calculations, inverse-variance meta-analysis inputs, robustness and sensitivity analyses, screening and exclusion audits, evidence-identifiability assessments, supplementary tables, figure source data, and Python code used for reproducible analyses. The systematic review identified 4,128 unique records and reconciled 103 report records into 97 independent study clusters. Primary inverse-variance synthesis was restricted to 12 independent studies with sufficiently identifiable treatment arms, exact means, uncertainty measures, sample sizes, and defensible comparators. Formal interaction evidence was available from four unique studies. These materials are provided to support transparency, reproducibility, independent verification, and reuse of the evidence framework. Copyrighted full-text articles are not redistributed.
Files
Steps to reproduce
Download and extract the complete data and code archive. Consult the README file for the structure and contents of the deposited materials. Use the provided reconciled evidence map and exact-data analysis inputs to reproduce the study-level quantitative dataset. Run the supplied Python analysis scripts using the included tabulated inputs. The scripts reproduce effect-size calculations, study-level aggregation, inverse-variance meta-analysis, heterogeneity estimation, correlation sensitivity analyses, leave-one-study-out analyses, contamination-provenance sensitivity analyses, and the corresponding figure source data. Supplementary tables document screening, study reconciliation, exclusions, treatment-arm structure, environmental relevance, robustness analyses, and evidence-identifiability assessments. Numerical results should be compared with the values reported in the accompanying manuscript and supplementary tables. No copyrighted full-text articles are required to execute the deposited analytical workflow and no copyrighted source PDFs are redistributed in this archive.
Institutions
- Kunming University of Science and TechnologyYunnan, Kunming