A large language model-based tool for identifying relationships to industry in research on the carcinogenicity of benzene, cobalt, and aspartame

LLM-based tools can significantly expedite and bolster the detection of disclosed conflicts of interest from industry sponsored research in cancer prevention. Possible use cases include facilitating the assessment of bias from industry studies in evidence synthesis reviews and alerting scientists to the influence of industry on scientific inference. Persistent challenges in ascertaining conflicts of interest underscore the urgent need for standardized, transparent, and enforceable disclosures in biomedical journals.