{ "_id": "6a129bf0acfb0bcc41d0eb2c", "Package": "AIGENIE", "Type": "Package", "Title": "Automatic Item Generation and Validation via Network-Integrated\nEvaluation", "Version": "2.1.0", "Date": "2026-03-10", "Authors@R": "c(\nperson(\"Lara\", \"Russell-Lasalandra\", email = \"llr7cb@virginia.edu\",\nrole = \"cre\", comment = c(ORCID = \"0009-0000-3014-1937\")),\nperson(\"Alexander\", \"Christensen\", role = \"aut\",\ncomment = c(ORCID = \"0000-0002-9798-7037\")),\nperson(\"Hudson\", \"Golino\", role = \"aut\",\ncomment = c(ORCID = \"0000-0002-1601-1447\"))\n)", "Description": "Automated psychological scale development and structural\nvalidation using large language models (LLMs) and network\npsychometric methods. Implements the AI-GENIE framework\n(Automatic Item Generation and Validation via\nNetwork-Integrated Evaluation) to generate candidate items,\ncompute embedding representations, and estimate dimensional\nstructure using Exploratory Graph Analysis (EGA). Item quality\nis evaluated using Unique Variable Analysis to identify\nredundant items and Bootstrap EGA to assess item and dimension\nstability. Supports both fully automated item generation and\nanalysis of user-provided item sets, facilitating efficient,\ntheory-informed measurement development prior to empirical data\ncollection.", "License": "AGPL (>= 3)", "Encoding": "UTF-8", "URL": "https://github.com/laralee/AIGENIE", "BugReports": "https://github.com/laralee/AIGENIE/issues", "Roxygen": "list(markdown = TRUE)", "RoxygenNote": "7.3.3", "Config/testthat/edition": "3", "Config/pak/sysreqs": "cmake libglpk-dev make libicu-dev libjpeg-dev\nlibpng-dev libuv1-dev libxml2-dev libssl-dev python3", "Repository": "https://laralee.r-universe.dev", "Date/Publication": "2026-05-22 18:29:38 UTC", "RemoteUrl": "https://github.com/laralee/AIGENIE", "RemoteRef": "HEAD", "RemoteSha": "e72bb46f2965d2dcfe6aa7a859b6b8c1c56257a7", "NeedsCompilation": "no", "Packaged": { "Date": "2026-05-24 06:29:11 UTC", "User": "root" }, "Author": "Lara Russell-Lasalandra [cre] (ORCID:\n),\nAlexander Christensen [aut] (ORCID:\n),\nHudson Golino [aut] (ORCID: 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local LLM (no API calls)", "topics": [ "local_chat" ] }, { "page": "local_GENIE", "title": "Local Generative Network-Integrated Evaluation (local_GENIE)", "topics": [ "local_GENIE" ] }, { "page": "main.prompts_validate", "title": "Validate and Normalize 'main.prompts'", "topics": [ "main.prompts_validate" ] }, { "page": "max.tokens_validate", "title": "Check that max.tokens is an integer", "topics": [ "max.tokens_validate" ] }, { "page": "plot_comparison", "title": "Plot Comparisons", "topics": [ "plot_comparison" ] }, { "page": "plot_stability_comparison", "title": "Plot Stability Comparison (network + item stability dotplot, side by side)", "topics": [ "plot_stability_comparison" ] }, { "page": "print_results", "title": "Print Results", "topics": [ "print_results" ] }, { "page": "python_env_info", "title": "Get AI-GENIE Python Environment Info", "topics": [ "python_env_info" ] }, { "page": "reduce_redundancy_uva", "title": "Reduce Redundancy via Iterative UVA (with Redundant Pair 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