AI Article Synopsis
- Cassava Sciences has been fined $40 million by an agency.
- The fine happened because they were promoting their drug, simufilam, based on research that wasn't good.
- This means they might have lied or exaggerated about how effective their drug is.
Article Abstract
Agency fines Cassava Sciences $40 million for touting flawed research on simufilam.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1126/science.adt5694 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Article Synopsis
- Cassava Sciences has been fined $40 million by an agency.
- The fine happened because they were promoting their drug, simufilam, based on research that wasn't good.
- This means they might have lied or exaggerated about how effective their drug is.
Great expectations: Past wages and unemployment durations.
Labour Econ
December 2011
Department of Economics, Johannes Kepler University Linz, Austria.
Decomposing wages into worker and firm wage components, we find that firm-fixed components are sizeable parts of workers' wages. If workers can only imperfectly observe the extent of firm-fixed components in their wages, they might be misled about the overall wage distribution. Such misperceptions may lead to unjustified high reservation wages, resulting in overly long unemployment durations.
View Article and Find Full Text PDFHealth risk assessment of electromagnetic fields: a conflict between the precautionary principle and environmental medicine methodology.
Rev Environ Health
February 2011
Unité Law Firm, Kungsbacka, Sweden.
The purpose of the precautionary principle is that legal requirements are to be made to safeguard against the possible health risks that have not yet been scientifically established. That a risk is not established cannot, therefore, be used as an excuse for not applying the principle. Yet, that rationale is exactly what is happening in the case of the possible health risks from exposure to electromagnetic fields (EMF).
View Article and Find Full Text PDFEstimating test-retest reliability in functional MR imaging. I: Statistical methodology.
Magn Reson Med
September 1997
Department of Statistics, Carnegie Mellon University, Pittsburgh, PA 15213, USA.
A common problem in the analysis of functional magnetic resonance imaging (fMRI) data is quantifying the statistical reliability of an estimated activation map. While visual comparison of the classified active regions across replications of an experiment can sometimes by informative, it is typically difficult to draw firm conclusions by inspection; noise and complex patterns in the estimated map make it easy to be misled. Here, several statistical models, of increasing complexity, are developed, under which "test-retest" reliability can be meaningfully defined and quantified.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!