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

From LIMSWiki
Jump to navigationJump to search
(Updated article of the week text.)
(Updated article of the week text)
(371 intermediate revisions by the same user not shown)
Line 1: Line 1:
<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig2 Wenig BMCBioinformatics2010 11.jpg|240px]]</div>
<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig1 Niszczota EconBusRev23 9-2.png|240px]]</div>
'''"[[Journal:OpenChrom: A cross-platform open source software for the mass spectrometric analysis of chromatographic data|OpenChrom: A cross-platform open source software for the mass spectrometric analysis of chromatographic data]]"'''
'''"[[Journal:Judgements of research co-created by generative AI: Experimental evidence|Judgements of research co-created by generative AI: Experimental evidence]]"'''


Today, data evaluation has become a bottleneck in [[Chromatography|chromatographic science]]. Analytical instruments equipped with automated samplers yield large amounts of measurement data, which needs to be verified and analyzed. Since nearly every [[Gas chromatography–mass spectrometry|GC/MS]] instrument vendor offers its own data format and software tools, the consequences are problems with data exchange and a lack of comparability between the analytical results. To challenge this situation a number of either commercial or non-profit software applications have been developed. These applications provide functionalities to import and analyze several data formats but have shortcomings in terms of the transparency of the implemented analytical algorithms and/or are restricted to a specific computer platform. ('''[[Journal:OpenChrom: A cross-platform open source software for the mass spectrometric analysis of chromatographic data|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 />
<br />
''Recently featured'':
''Recently featured'':  
{{flowlist |
: ▪ [[Journal:Custom software development for use in a clinical laboratory|Custom software development for use in a clinical laboratory]]
* [[Journal:Geochemical biodegraded oil classification using a machine learning approach|Geochemical biodegraded oil classification using a machine learning approach]]
: ▪ [[Journal:NG6: Integrated next generation sequencing storage and processing environment|NG6: Integrated next generation sequencing storage and processing environment]]
* [[Journal:Knowledge of internal quality control for laboratory tests among laboratory personnel working in a biochemistry department of a tertiary care center: A descriptive cross-sectional study|Knowledge of internal quality control for laboratory tests among laboratory personnel working in a biochemistry department of a tertiary care center: A descriptive cross-sectional study]]
: ▪ [[Journal:STATegra EMS: An experiment management system for complex next-generation omics experiments|STATegra EMS: An experiment management system for complex next-generation omics experiments]]
* [[Journal:Sigma metrics as a valuable tool for effective analytical performance and quality control planning in the clinical laboratory: A retrospective study|Sigma metrics as a valuable tool for effective analytical performance and quality control planning in the clinical laboratory: A retrospective study]]
}}

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...)
Recently featured: