academic-researcher

Data extraction from PDFs pulls structured metadata like authors, year, title, venue, sample sizes, and study type into JSON format. This Skill automates extraction from cybersecurity fatigue research papers, parsing participant groups, fatigue measurements, and correlations to save results as parsed_papers.json for further analysis.

Statistical correlation analysis captures reported r-values and p-values from study data, then computes correlations across participant groups and fatigue metrics. This Skill processes extracted paper data and outputs correlation_analysis.json with computed relationships ready for statistical interpretation.

Organizing fatigue study data requires extracting and grouping participant cohorts, experience levels, fatigue measurements, and sample sizes into a consistent structure. This Skill structures data from PDFs into JSON conforming to exact formats, enabling comparison across IT security professionals, general IT staff, and non-technical groups.

Yes, this Skill processes PDFs of fatigue studies using PyPDF2 to extract text, tables, and metadata. It parses authors, venues, participant details, and reported statistics from academic paper PDFs into structured JSON outputs compatible with the research toolkit.

Required inputs are PDF files of cybersecurity fatigue research papers placed in the papers/ directory. The Skill requires PyPDF2, scipy, and numpy; it outputs parsed_papers.json and correlation_analysis.json to the results/ directory for downstream statistical analysis.

Correlation analysis across groups extracts fatigue and experience metrics for IT security professionals, general IT staff, and non-technical cohorts, then computes r and p-values per group. This Skill enables comparative statistical analysis across study populations in a single correlation_analysis.json output.