Difference between revisions of "Template:Article of the week"

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<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig2 Matielo Publications2018 6-4.png|240px]]</div>
<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig1 Niszczota EconBusRev23 9-2.png|240px]]</div>
'''"[[Journal:A bibliometric analysis of Cannabis publications: Six decades of research and a gap on studies with the plant|A bibliometric analysis of ''Cannabis'' publications: Six decades of research and a gap on studies with the plant]]"'''
'''"[[Journal:Judgements of research co-created by generative AI: Experimental evidence|Judgements of research co-created by generative AI: Experimental evidence]]"'''


In this study we performed a bibliometric analysis focusing on the general patterns of scientific publications about ''[[wikipedia:Cannabis|Cannabis]]'', revealing their trends and limitations. Publications related to ''Cannabis'', released from 1960 to 2017, were retrieved from the Scopus database using six search terms. The search term “[[wikipedia:Genetics|Genetics]]” returned 53.4% of publications, while “forensic genetics” and “[[wikipedia:Traceability|traceability]]” represented 2.3% and 0.1% of the publications, respectively. However, 43.1% of the studies were not directly related to ''Cannabis'' and, in some cases, ''Cannabis'' was just used as an example in the text. A significant increase in publications was observed after 2001, with most of the publications coming from Europe, followed by North America. Although the term "''Cannabis''" was found in the title, abstract, or keywords of 1284 publications, we detected a historical gap in studies on the plant. ('''[[Journal:A bibliometric analysis of Cannabis publications: Six decades of research and a gap on studies with the plant|Full article...]]''')<br />
The introduction of [[ChatGPT]] has fuelled a public debate on the appropriateness of using generative [[artificial intelligence]] (AI) ([[large language model]]s or LLMs) in work, including a debate on how they might be used (and abused) by researchers. In the current work, we test whether delegating parts of the research process to LLMs leads people to distrust researchers and devalues their scientific work. Participants (''N'' = 402) considered a researcher who delegates elements of the research process to a PhD student or LLM and rated three aspects of such delegation. Firstly, they rated whether it is morally appropriate to do so. Secondly, they judged whether—after deciding to delegate the research process—they would trust the scientist (who decided to delegate) to oversee future projects ... ('''[[Journal:Judgements of research co-created by generative AI: Experimental evidence|Full article...]]''')<br />
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Latest revision as of 15:26, 20 May 2024

Fig1 Niszczota EconBusRev23 9-2.png

"Judgements of research co-created by generative AI: Experimental evidence"

The introduction of ChatGPT has fuelled a public debate on the appropriateness of using generative artificial intelligence (AI) (large language models or LLMs) in work, including a debate on how they might be used (and abused) by researchers. In the current work, we test whether delegating parts of the research process to LLMs leads people to distrust researchers and devalues their scientific work. Participants (N = 402) considered a researcher who delegates elements of the research process to a PhD student or LLM and rated three aspects of such delegation. Firstly, they rated whether it is morally appropriate to do so. Secondly, they judged whether—after deciding to delegate the research process—they would trust the scientist (who decided to delegate) to oversee future projects ... (Full article...)
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