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In contrast, the work presented here evaluates a complete set of different feature categories and each feature's relevance is calculated.
Relevance is calculated using Equation (13), which consists of two factors.
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Six properties of pharmaceutical relevance were calculated with MOE: hydrogen bond donors (HBD), hydrogen bond acceptors (HBA), the octanol and/or water partition coefficient (logP), molecular weight (MW), topological polar surface area (TPSA) and number of rotatable bonds (RTB).
Determination of common regions for "reward win" and "high personal relevance" was calculated by a conjunction analysis implemented in SPM2 for the contrasts "reward win > reward lose" and "high personal relevance > low personal relevance".
The level of clinical relevance was calculated using the effect size, in which an effect size of 0.20 0.49 reflected a small clinically relevant difference, an effect size of between 0.50 0.80 reflected a moderate clinically relevant difference and >0.80 reflected a large clinically relevant difference.
The keyword relevance score is calculated as the number of matching terms divided by the logarithm of the number of unique words in the keywords list of an entry (see the PostgreSQL manual).
For each method, the maximal value of f-measure on the overall threshold of relevance, Fmax, is calculated as (8) F max = max t { 2 · pr (t ) · rc (t ) pr (t ) + rc (t ) }. Considering the relationships between GO terms, the comparisons are guided by the true path rule.
For each pair of adjacent points, the relevance measure R is calculated.
A protein's cancer relevance score r p is calculated as the function (1).
Each image's overall relevance to this query is calculated using Eq. 10.
As a result, a vector corresponding to the relevance of the frequency axis is calculated.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com