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<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Denuders.jpg|200px]]</div>
<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig1 Niszczota EconBusRev23 9-2.png|240px]]</div>
A '''[[denuder]]''' is a cylindrical or annular conduit or tube internally coated with a reagent that selectively reacts with a stable flow of gas drawn through the conduit. The gas molecules diffuse to the walls while the [[analyte]] contained in the gas is transmitted outwards via laminar flow, collected, and analyzed. Effectiveness of the system depends primarily "on a complete discrimination between the gas species and particulate matter."
'''"[[Journal:Judgements of research co-created by generative AI: Experimental evidence|Judgements of research co-created by generative AI: Experimental evidence]]"'''


Additional non-linear denuder geometries have also been tried with mixed results. Coiled configurations increased collection efficiency but lost larger particulate. A parallel multi-tube diffusion denuder has also been tried and found to increase collection efficiency. Other geometries include honeycombed, annular, and parallel plate. The development of the annular denuder in particular allowed researchers to overcome the inefficiencies of cylindrical denuders, allowing operation at larger flow rates (up to 30 times that of cylindrical denuders), shorter sampling periods, and less particle loss. ('''[[Denuder|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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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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