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Fatigue life predictions were made using a two-layer model based on case and core material fatigue properties and compared to the experimental results.
For each task, we constructed two datasets based on case and control groups of individuals.
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Central to our model is a view of the relationship between cases, rules based on cases, and the social values which justify those rules.
Here, we report the analysis based on cases and controls.
These results are mostly based on cases and controls of European descent.
The remaining analyses are based on cases and controls who reported to have drunk alcohol in the preceding year; 422 cases and 1725 controls (total n = 2147).
A subanalysis based on cases and controls younger than 70 years of age, with data on first birth and number of children, showed similar risk estimates even after adjustment for age at first birth and parity.
Based on cases and controls, the risk of BCC increased with increasing lifetime concentration of arsenic in drinking water (OR 1.2 per 10 µg/L increase, 95% CI 1.1 1.3), as previously presented [Leonardi et al., 2012].
However, these guidelines are mostly based on case reports and retrospective studies and therefore graded at a low level of evidence.
In an attempt to emulate this expertise and reasoning, a CDSS based on case matching and recommendations, or case-based reasoning (CBR), was developed.
Experience remains scarce and is mostly based on case reports and small series.
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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