AI-assisted systematic review screening tool
The Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) statement, published in 2009, was designed to help systematic reviewers transparently report why the review was done, what the authors did, and what they found. Over the past decade, advances in systematic review methodology and terminology have necessitated an update to the guideline. The PRISMA 2020 statement replaces the 2009 statement and includes new reporting guidance that reflects advances in methods to identify, select, appraise, and synthesise studies. The structure and presentation of the items have been modified to facilitate implementation. In this article, we present the PRISMA 2020 27-item checklist, an expanded checklist that details reporting recommendations for each item, the PRISMA 2020 abstract checklist, and the revised flow diagrams for original and updated reviews.
The PRISMA 2020 statement: an updated guideline for reporting systematic reviews
Complete dataset including search results, ASReview project, screening decisions, and nanopub URIs. DOI: 10.5281/zenodo.18070378
Source code repository containing all Jupyter notebooks, configuration templates, and documentation
Systematic Review Pipeline - GitHub Repository
JSON configuration for quantum computing + biodiversity PICO question
JSON configuration with API endpoints and result counts
JSON configuration with search terms, databases, and date ranges
JSON with study characteristics and quality assessment
Extracts screening decisions from ASReview project file
Create of a nanopublication for storing the results of a bibliography search. A nanopublication is created for each database search.
Generates PICO research question nanopublication from JSON config
Queries OpenAlex, arXiv, PubMed, Europe PMC, Semantic Scholar APIs
Generates search execution dataset nanopublication
Generates search strategy nanopublication with Boolean queries
Generates study assessment dataset nanopublication
Generates individual nanopubs for each included/excluded study
Python package dependencies: pandas, numpy, requests, rdflib, nanopub, asreview, jupyter
Illustration of Quantum Computingfor Biodiversity. This illustration was generated by Perplexity.ai on 29th December 2025.
Quantum Computing applied to Biodiversity
Published nanopub documenting the search strategy
Published nanopub defining the research question
Published nanopub with search execution metadata
Published nanopub with aggregated study characteristics
A PRISMA-compliant scoping review investigating applications of quantum computing in biodiversity and ecological research. This Research Object contains the complete reproducible workflow from research question to study assessment, implemented as a pipeline of Jupyter notebooks with nanopublication outputs for transparent, machine-readable documentation. Screening: 1,649 records → 569 screened → 283 included → 238 nanopubs published.
Quantum Computing Applications in Biodiversity Research - Scoping Review
Fouilloux, Anne. "Quantum Computing Applications in Biodiversity Research - Scoping Review." ROHub. Dec 27 ,2025. https://w3id.org/ro-id/b6e01d7a-9f25-4b37-82df-32ef2e7171e3.
API queries and search result aggregation
Search strategy with Boolean operators and database selection
Study characteristics and quality assessment
Included/excluded study nanopublications
PICO framework research question definition
Aggregated search results from all databases
ASReview LAB project with screening decisions
Extracted inclusion/exclusion decisions with reasons
Index of all published study inclusion nanopublications