https://w3id.org/np/RAxofFvB6w26DJT9XW0As3CqzcwwR7IKL3cfKVHvAE0hc/Head https://w3id.org/np/RAxofFvB6w26DJT9XW0As3CqzcwwR7IKL3cfKVHvAE0hc http://www.nanopub.org/nschema#hasAssertion https://w3id.org/np/RAxofFvB6w26DJT9XW0As3CqzcwwR7IKL3cfKVHvAE0hc/assertion https://w3id.org/np/RAxofFvB6w26DJT9XW0As3CqzcwwR7IKL3cfKVHvAE0hc http://www.nanopub.org/nschema#hasProvenance https://w3id.org/np/RAxofFvB6w26DJT9XW0As3CqzcwwR7IKL3cfKVHvAE0hc/provenance https://w3id.org/np/RAxofFvB6w26DJT9XW0As3CqzcwwR7IKL3cfKVHvAE0hc http://www.nanopub.org/nschema#hasPublicationInfo https://w3id.org/np/RAxofFvB6w26DJT9XW0As3CqzcwwR7IKL3cfKVHvAE0hc/pubinfo https://w3id.org/np/RAxofFvB6w26DJT9XW0As3CqzcwwR7IKL3cfKVHvAE0hc http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://www.nanopub.org/nschema#Nanopublication https://w3id.org/np/RAxofFvB6w26DJT9XW0As3CqzcwwR7IKL3cfKVHvAE0hc/assertion https://w3id.org/np/RAwQj3SNiopwPrHXfoRT2JtYZSt-5JsDHjBDW6nYz_rDE/studyAssessmentDataset http://purl.org/dc/terms/created 2026-01-10 https://w3id.org/np/RAwQj3SNiopwPrHXfoRT2JtYZSt-5JsDHjBDW6nYz_rDE/studyAssessmentDataset http://purl.org/dc/terms/hasExtractionMethod Manual full-text reading of selected papers with systematic quote extraction. Quotes selected to provide direct evidence for specific PICO evaluation framework dimensions (application domains, computational advantages demonstrated, hardware requirements, scalability assessments, readiness for operational research). Each quote documented with: (1) exact quoted text from paper, (2) interpretation explaining relevance to PICO research question and evaluation framework, (3) connection to specific evaluation dimensions. Quote extraction focused on: empirical results demonstrating computational advantages, technical details on hardware requirements and limitations, methodological approaches enabling cross-domain applications, practical considerations for operational deployment. All quotes and interpretations published as individual comment nanopublications linked to source papers. https://w3id.org/np/RAwQj3SNiopwPrHXfoRT2JtYZSt-5JsDHjBDW6nYz_rDE/studyAssessmentDataset http://purl.org/dc/terms/hasQualityAssessment Papers assessed for relevance to PICO criteria and quality of evidence for quantum computing applications in biodiversity research. Assessment criteria included: (1) Clarity of methods - well-documented quantum algorithms and experimental setup, (2) Strength of evidence for computational advantages - quantitative comparisons between quantum and classical approaches (e.g., 19/20 performance comparisons), (3) Transferability to biodiversity contexts - explicit discussion of ecological/biodiversity applications or clear methodological parallels between demonstrated applications (disease networks) and target applications (ecological networks), (4) Hardware requirements documentation - discussion of current limitations (NISQ devices, qubit counts, partitioning strategies) and practical workarounds, (5) Transparency about limitations - acknowledgment of challenges such as state preparation bottlenecks, performance variability, and dependency on future hardware improvements. Both selected papers provided high-quality evidence across multiple evaluation dimensions with clear documentation of both advantages and limitations. https://w3id.org/np/RAwQj3SNiopwPrHXfoRT2JtYZSt-5JsDHjBDW6nYz_rDE/studyAssessmentDataset http://purl.org/dc/terms/hasStudyResults LLM-based PDF screening of 283 papers from title/abstract screening resulted in 2 papers marked as INCLUDE. Both papers selected for detailed full-text analysis with systematic quote extraction and interpretation generation. Selected papers: (1) QOMIC: quantum optimization for motif identification - DOI: https://doi.org/10.1093/bioadv/vbae208, Study Nanopub: https://w3id.org/np/RAvZd0nKPT, Published: 2024 - Selected for replication study and technology readiness assessment (https://doi.org/10.5281/zenodo.18157621, Replication Study Nanopub: https://w3id.org/np/RAWsF2T9Rp9iKz78AQgad-SZjl4MXtocBRcZWW2cNl2Dw); (2) Addressing ecological challenges from a quantum computing perspective - DOI: https://doi.org/10.48550/arXiv.2504.03866, Study Nanopub: https://w3id.org/np/RA382F5M0J, Published: 2025. These papers provided evidence across multiple PICO evaluation framework dimensions including computational advantages demonstrated (19/20 comparisons showing quantum advantage), hardware requirements (qubit limitations, NISQ devices), application domains (statistical tools, network analysis, dynamical systems), and readiness for operational research (state preparation bottlenecks, practical workarounds). From these 2 papers, 7 detailed quotes were extracted with interpretations documenting specific evidence for evaluation framework dimensions. https://w3id.org/np/RAwQj3SNiopwPrHXfoRT2JtYZSt-5JsDHjBDW6nYz_rDE/studyAssessmentDataset http://purl.org/dc/terms/isPartOf https://w3id.org/spaces/sciencelive/quantum-biodiversity-review https://w3id.org/np/RAwQj3SNiopwPrHXfoRT2JtYZSt-5JsDHjBDW6nYz_rDE/studyAssessmentDataset http://www.w3.org/1999/02/22-rdf-syntax-ns#type https://w3id.org/sciencelive/o/terms/StudyAssessmentDataset https://w3id.org/np/RAwQj3SNiopwPrHXfoRT2JtYZSt-5JsDHjBDW6nYz_rDE/studyAssessmentDataset http://www.w3.org/2000/01/rdf-schema#label Study Assessment Dataset: Full-Text PDF Screening Against PICO - Quantum Computing for Biodiversity https://w3id.org/np/RAwQj3SNiopwPrHXfoRT2JtYZSt-5JsDHjBDW6nYz_rDE/studyAssessmentDataset https://w3id.org/sciencelive/o/terms/followsEligibilityCriteria Full-text PDF screening of included studies from title/abstract screening (Study Assessment Dataset RAlN5rGFTl). Papers assessed against PICO criteria (https://w3id.org/np/RAvk9pmoZ2IberoDe7zUWV0bVithiy6CnbSG5y06YuKM0) using PDF-based full-text analysis. INCLUSION: Papers with accessible PDFs; Papers addressing quantum computing methods applied to biodiversity research domains (PICO Population); Papers demonstrating quantum or quantum-inspired approaches (PICO Intervention) with comparison to classical methods (PICO Comparator); Papers providing evidence for evaluation framework dimensions (application domains, computational advantages, hardware requirements, scalability, readiness). EXCLUSION: PDFs not accessible; Papers not matching PICO Population, Intervention, or Comparator; Papers without sufficient detail for evaluation against evaluation framework; Papers lacking evidence for computational advantages or biodiversity applications. https://w3id.org/np/RAwQj3SNiopwPrHXfoRT2JtYZSt-5JsDHjBDW6nYz_rDE/studyAssessmentDataset https://w3id.org/sciencelive/o/terms/hasDatasetFileLocation https://doi.org/10.5281/zenodo.18674700 https://w3id.org/np/RAwQj3SNiopwPrHXfoRT2JtYZSt-5JsDHjBDW6nYz_rDE/studyAssessmentDataset https://w3id.org/sciencelive/o/terms/hasLimitations Limited to papers with accessible PDFs - some included papers from title/abstract screening may not have been available for full-text analysis or PDF retrieval may have failed. LLM-based screening introduces potential for interpretation variance and may have different inclusion thresholds compared to human-only screening. Selection criteria prioritized papers that clearly addressed quantum computing methods (PICO Intervention) applied to biodiversity/ecological domains (PICO Population) with demonstrated computational advantages. The LLM screening resulted in only 2 INCLUDE papers from 283 screened, reflecting stringent matching against PICO criteria. No inter-rater reliability assessment performed (single screener using LLM assistance). The QOMIC paper was selected for replication study based on having empirical quantitative results (19/20 performance comparisons) suitable for technology readiness assessment. https://w3id.org/np/RAwQj3SNiopwPrHXfoRT2JtYZSt-5JsDHjBDW6nYz_rDE/studyAssessmentDataset https://w3id.org/sciencelive/o/terms/hasStudyCharacteristics Input: 283 papers from title/abstract screening (Study Assessment Dataset: https://w3id.org/np/RAlN5rGFTl). Method: PDF-based full-text screening against PICO criteria using LLM evaluation. LLM screening outcome: 2 papers marked as INCLUDE, both selected for detailed quote extraction and analysis. Study types: Original research on quantum optimization algorithms for biological network analysis; Perspective/review papers on quantum computing applications in ecological modeling and biodiversity research. Domains covered: Quantum optimization (QAOA), quantum machine learning, ecological network analysis, species distribution modeling, conservation optimization. Time range: Papers published 2024-2025. Replication study conducted on QOMIC paper to assess technology readiness for biodiversity applications. https://w3id.org/np/RAwQj3SNiopwPrHXfoRT2JtYZSt-5JsDHjBDW6nYz_rDE/studyAssessmentDataset https://w3id.org/sciencelive/o/terms/usesAssessmentTechnique LLM-based full-text screening using PDF analysis. Tool: Python screening pipeline (scanning_papers_main.ipynb with screeningPaper module). Method: Automated PDF retrieval attempted for papers from title/abstract screening; LLM (via Ollama) evaluation of full text against PICO criteria with focus on Population and Intervention matching; Decision output: INCLUDE/EXCLUDE with confidence score and reasoning; Papers passing screening were selected for detailed quote extraction and comment generation. PICO criteria used: https://w3id.org/np/RAvk9pmoZ2IberoDe7zUWV0bVithiy6CnbSG5y06YuKM0. Screeners: 1 (Anne Fouilloux). 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