Data and code for: Integrating hazard into the foodome: a critical review of AI pipelines for chemical, nutritional and safety characterization of foods, with a FAIR audit of data infrastructures

This repository contains the data and code supporting the manuscript "Integrating hazard into the foodome: a critical review of AI pipelines for chemical, nutritional and safety characterization of foods, with a FAIR audit of data infrastructures" (submitted to Information Processing & Management, manuscript ID IPM-D-26-04358). The package is organised in two folders. The first covers the literature corpus construction pipeline: raw and processed corpora at five stages, extraction, filtering and screening scripts, the four LLM prompts, screening outputs, calibration data, run manifests, bibliometric analysis artefacts, and the wheat case study data. The second covers the FAIR compliance audit: the manual audit verdicts, per-database drift reports, audit manifests, correction application journals, and the raw responses of the automated FAIR scoring instruments. All files are listed with their relative path, size and SHA-256 checksum in MANIFEST.md.