{
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  "affiliations": [
    "Department of Mathematics and Data Science, Vrije Universiteit Brussel",
    "Department of Mathematics, Computer Science and Statistics, Ghent University",
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  "bibtex": "https://research.draconitic.com/paper/0ewmn716zw2cy.bib",
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  "doi": "10.1080/00031305.2026.2700237",
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  "landing_url": "https://arxiv.org/abs/2404.11150",
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  "pdf_url": "https://arxiv.org/pdf/2404.11150",
  "pmcid": null,
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  "published": "2026-07-08",
  "publisher": "Taylor & Francis",
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  "subjects": [
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  "title": "Automated, Efficient, and Model-Free Inference for Randomized Clinical Trials via Data-Driven Covariate Adjustment",
  "title_text": "Automated, Efficient, and Model-Free Inference for Randomized Clinical Trials via Data-Driven Covariate Adjustment",
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  "venue": "The American Statistician",
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