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Categorical variables depict clinical parameters with multiple subtypes but no clear ordering (e.g., smoking history), ordinal describes clinical parameters with multiple subtypes with identifiable ordering (e.g., clinical stage), and binary represents clinical parameters with only two subtypes (e.g., gender).
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In this paper, the public signal is binary, representing whether the statistical test is passed or not.
In the present work, x ji are binary, representing the absence or presence of a chemical atom environment descriptors in the ligand.
The covariate was binary, representing either plots that initially included a legume or plots initiated without a legume and subsequently colonized by one (the 4 plots that were not initiated or colonized by a legume were excluded from this analysis).
Each binary classifier represents a decision function for one of the concepts.
The SADs between two binary molds represents the total number of mismatched pixels.
The binary network represents direct interactions between two proteins.
The use of statistical significance as a binary outcome represents another potential limitation.
In principle, the intersection of the six binary datasets represents the stable nucleosome distribution among these datasets.
The magnitude of the current through the GNR functions as the binary gate output, with binary 1 representing the large current of the conductive FM state and binary 0 representing the resistive AFM state.
The prefixes "US" and "S" indicate whether the parameter is considered unsigned binary number or signed binary number represented in two's complement representation.
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