Survey of 868 scientific programmers shows generative AI adoption is highest among the inexperienced, who prefer conversational tools, and perceived productivity correlates most with volume of accepted generated code rather than validation practices.
PLOS Computational Biology 13(6), e1005510 (Jun 2017)
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SurvBench supplies a configurable, open-source preprocessing pipeline that standardizes multi-modal EHR data from four critical-care databases for single-risk and competing-risk survival analysis.
An integrated workflow using version control, code review, automated testing, structured logging, metadata-rich output, and standardized post-processing creates a FAIR-aligned provenance chain from code development to published figures in numerical physics simulations.
Mathematical proofs are inherently reproducible by nature, unlike computational experiments which require shared code for equivalent scientific diligence.
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A survey of generative AI adoption and perceived productivity among scientists who program
Survey of 868 scientific programmers shows generative AI adoption is highest among the inexperienced, who prefer conversational tools, and perceived productivity correlates most with volume of accepted generated code rather than validation practices.
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SurvBench: A Standardised Preprocessing Pipeline for Multi-Modal Electronic Health Record Survival Analysis
SurvBench supplies a configurable, open-source preprocessing pipeline that standardizes multi-modal EHR data from four critical-care databases for single-risk and competing-risk survival analysis.
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From Code to Figure: A FAIR-Aligned Data Provenance Chain for Reproducible Simulation Research in Numerical Physics
An integrated workflow using version control, code review, automated testing, structured logging, metadata-rich output, and standardized post-processing creates a FAIR-aligned provenance chain from code development to published figures in numerical physics simulations.
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Truth, Proof, and Reproducibility: There's no counter-attack for the codeless
Mathematical proofs are inherently reproducible by nature, unlike computational experiments which require shared code for equivalent scientific diligence.