An internal validation study of a staged, auditable workflow for systematic reviews. The study reports performance metrics, workload reduction, preservation of final inclusions, and error patterns across review stages. The dataset was authored by Vinicius Remus Ballotin and is available under a CC-BY-4.0 license.
Use Cases
- Validate automated deduplication algorithms based on reported performance metrics
- Benchmark workload reduction tools against the staged workflow results
- Analyze error patterns in systematic review screening stages
Strengths
- Validates a workflow against human reviewer decisions, providing a concrete benchmark
- Released under a permissive CC-BY-4.0 license
Limitations
- Description metadata is limited; actual data quality requires manual inspection after download
- Column-level documentation is absent; field semantics must be inferred after download
Provenance
- Source
- figshare
- Freshness
- Last updated 2026-05-31 21:28:49; freshness should be verified