Sentence examples for described a causal from inspiring English sources

Exact(1)

Numerous authors have described a causal relation between malrotation of the femoral component and patellofemoral complications in TKA [ 1, 3, 4, 7, 18, 23].

Similar(59)

It describes a causal representation of the phenomena involved in the degradation process.

Arguably one of the first systematic attempts was Wilken's (1979) model to describe a causal relation between entrepreneurship and economic growth.

Rather than the cognitive mental process used to describe the British government's action, this CAC relies on the emotive power of "fear" to describe a causal relationship between the merchants' reality and possible outcomes of rebellion in the colonies.

Epidemiologic studies are generally ill-suited to describe a causal marker when multiple correlated markers, all with little if any known functional relevance to the phenotype in question, exist.

We describe a causal relation between CYT-1 expressionession and tumorigenesis in transgenic mice.

If the LMM/GLMM describes observed random subclusters of size n and, then and describe a causal effect of in observed random subclusters of size n.

Neither was our study set up to describe a causal relationship between the safety programmes and other initiatives over the years and our study outcome, AEs and preventable AEs.

In contrast, the next sentence not only points to a temporal relationship in which phosphorylation happens before the interaction but also describes a causal relation (i.e. how the interaction is a consequence of the phosphorylation): Bad phosphorylation induced by survival factors leads to its preferential binding to 14-3-3 14-3-3 14-3-3on of the deand-inducing function of Bad.

This model describes a causal pathway where team members can be seen to move from sharing information, to identifying a problem that threatens the safety of care, to decision- making to resolve that problem, and finally to follow-up actions to enact the new plan [ 21].

We have described a dynamic causal model for SC changes that includes anticipatory, evoked, and spontaneous skin conductance changes and allows, via model inversion, estimation of the most likely neural contributions to each of these components.

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