Ai Feedback
Exact(6)
Exposure misclassification is an inherent disadvantage of time-series studies.
Thus, phthalate exposure misclassification is an important consideration in epidemiological studies.
One possible explanation for this misclassification is an often observed simplification of multiracial heritage.
Histologic misclassification is an unavoidable problem when developing tissue-based biomarkers if histologic readings are to be the "gold standard" against which the biomarker is to be measured.
49 Such misclassification is an important limitation given the short duration of gestation and even shorter duration of developmental "critical periods", during which birth defects can plausibly occur as a result of drug exposure.
However, such misclassification is an implausible explanation for our finding that advanced disease was proportionally twice as common in women as men, as one would have to postulate that clinical and radiological investigations were systematically better at identifying the early signs of advanced disease in women than in men.
Similar(54)
Covariate misclassification is a common problem in epidemiology, genetics, and other biomedical areas.
A misclassification is a feature that is classified as relevant by the feature selection procedure, whereas it is irrelevant or redundant according to the data generation procedure, and v.v.
DOL has explained that it believes misclassification is a significant problem which deprives many workers access to federal, state and local benefits and protections, such as family/medical leave, overtime, minimum wage, unemployment compensation and protection under employment anti-discrimination laws.
Misclassification is a serious problem in construction as well as other industries, and it is exacerbated by increasingly fissured employment structures where work is contracted and subcontracted away from the core company.
This misclassification is a recognized problem associated with online databases [84], [85].
Write better and faster with AI suggestions while staying true to your unique style.
Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com