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)
 
(144 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:Tab1 Montoya FrontPharm2020 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:Cannabis contaminants limit pharmacological use of cannabidiol|Cannabis contaminants limit pharmacological use of cannabidiol]]"'''
'''"[[Journal:Judgements of research co-created by generative AI: Experimental evidence|Judgements of research co-created by generative AI: Experimental evidence]]"'''


For nearly a century, [[wikipedia:Cannabis|cannabis]] has been stigmatized and [[wikipedia:Legality of cannabis|criminalized]] across the globe, but in recent years, there has been a growing interest in cannabis due to the therapeutic potential of [[wikipedia:Cannabinoid#Phytocannabinoids|phytocannabinoids]]. With this emerging interest in cannabis, concerns have arisen about the possible [[wikipedia:Contamination|contaminations]] of [[wikipedia:Hemp|hemp]] with [[wikipedia:Pesticide|pesticides]], [[wikipedia:Heavy metals|heavy metals]], microbial [[wikipedia:Pathogen|pathogens]], and [[wikipedia:Carcinogen|carcinogenic]] compounds during the [[wikipedia:Cannabis cultivation|cultivation]], manufacturing, and packaging processes. This is of particular concern for those turning to cannabis for [[wikipedia:Cannabis (drug)|medicinal purposes]], especially those with compromised immune systems. This review aims to provide types of contaminants and examples of cannabis contamination using case studies that elucidate the medical consequences consumers risk when using adulterated cannabis products. ('''[[Journal:Cannabis contaminants limit pharmacological use of cannabidiol|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'':
: ▪ [[Journal:Development of an informatics system for accelerating biomedical research|Development of an informatics system for accelerating biomedical research]]
{{flowlist |
: ▪ [[Journal:Mini-review of laboratory operations in biobanking: Building biobanking resources for translational research|Mini-review of laboratory operations in biobanking: Building biobanking resources for translational research]]
* [[Journal:Geochemical biodegraded oil classification using a machine learning approach|Geochemical biodegraded oil classification using a machine learning approach]]
: ▪ [[Journal:Extending an open-source tool to measure data quality: Case report on Observational Health Data Science and Informatics (OHDSI)|Extending an open-source tool to measure data quality: Case report on Observational Health Data Science and Informatics (OHDSI)]]
* [[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]]
}}

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...)
Recently featured: