Biomedical research aimed at improving human health is particularly reliant on publicly funded basic science, according to a new analysis boosted by artificial intelligence.
Citations represent the transfer of knowledge from one scientist to another. Citations are extensively catalogued and tracked to measure the significance of individual studies and of the individuals conducting them, but not all citations included in any given paper make equally important contributions to the research they describe.
Hutchins and his collaborators figured citations added later in the publication process, like those that appear at the behest of peer reviewers—the subject-matter experts that evaluatesubmitted to journals—are less likely to have been truly important to the authors' research. To make the early-late distinction, the researchers trained a machine learning algorithm to judge citations on their importance by feeding it citation information from a pool of more than 38,000 scholarly papers. Each paper'sdata came in two versions: a preprint version, posted publicly before peer review, and the eventual published version that had undergone peer review.
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