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

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A '''[[laboratory information system]] (LIS)''' is a software system that records, manages, and stores data for clinical [laboratory|laboratories]]. A LIS has traditionally been most adept at sending laboratory test orders to lab instruments, tracking those orders, and then recording the results, typically to a searchable database. The standard LIS has supported the operations of public health institutions (like [[hospital|hospitals]] and clinics) and their associated labs by managing and reporting critical data concerning "the status of infection, immunology, and care and treatment status of patients."
'''"[[Journal:Judgements of research co-created by generative AI: Experimental evidence|Judgements of research co-created by generative AI: Experimental evidence]]"'''


There is often confusion regarding the difference between a laboratory information system (LIS) and a [[laboratory information management system]] (LIMS). While the two laboratory informatics components are related, their purposes diverged early in their existences. Up until recently, LIMS and LIS have exhibited a few key differences, such as a LIS being designed primarily for processing and reporting data related to individual patients in a clinical setting, with a LIMS being traditionally designed to process and report data related to batches of samples from drug trials, water treatment facilities, and other entities that handle complex batches of data. However, distinctions between the two systems have faded somewhat as some LIMS vendors have adopted the case-centric information management normally reserved for a LIS, blurring the lines between the two components further. ('''[[Laboratory information system|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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''Recently featured'':
''Recently featured'': [[Denuder]], [[Infectious disease informatics]], [[National Institute for Occupational Safety and Health]]
{{flowlist |
* [[Journal:Geochemical biodegraded oil classification using a machine learning approach|Geochemical biodegraded oil classification using a machine learning approach]]
* [[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: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...)
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