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< h1 > Calculate the matching score for microorganisms< / h1 >
< small class = "dont-index" > Source: < a href = 'https://github.com/msberends/AMR/blob/master/R/mo_matching_score.R' > < code > R/mo_matching_score.R< / code > < / a > < / small >
< div class = "hidden name" > < code > mo_matching_score.Rd< / code > < / div >
< / div >
< div class = "ref-description" >
< p > This helper function is used by < code > < a href = 'as.mo.html' > as.mo()< / a > < / code > to determine the most probable match of taxonomic records, based on user input.< / p >
< / div >
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< pre class = "usage" > < span class = 'fu' > mo_matching_score< / span > (< span class = 'kw' > x< / span > , < span class = 'kw' > n< / span > )< / pre >
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< h2 class = "hasAnchor" id = "arguments" > < a class = "anchor" href = "#arguments" > < / a > Arguments< / h2 >
< table class = "ref-arguments" >
< colgroup > < col class = "name" / > < col class = "desc" / > < / colgroup >
< tr >
< th > x< / th >
< td > < p > Any user input value(s)< / p > < / td >
< / tr >
< tr >
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< th > n< / th >
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< td > < p > A full taxonomic name, that exists in < code > < a href = 'microorganisms.html' > microorganisms$fullname< / a > < / code > < / p > < / td >
< / tr >
< tr >
< th > uncertainty< / th >
< td > < p > The level of uncertainty set in < code > < a href = 'as.mo.html' > as.mo()< / a > < / code > , see < code > allow_uncertain< / code > in that function (here, it defaults to 1, but is automatically determined in < code > < a href = 'as.mo.html' > as.mo()< / a > < / code > based on the number of transformations needed to get to a result)< / p > < / td >
< / tr >
< / table >
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< h2 class = "hasAnchor" id = "matching-score-for-microorganisms" > < a class = "anchor" href = "#matching-score-for-microorganisms" > < / a > Matching score for microorganisms< / h2 >
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< p > With ambiguous user input in < code > < a href = 'as.mo.html' > as.mo()< / a > < / code > and all the < code > < a href = 'mo_property.html' > mo_*< / a > < / code > functions, the returned results are chosen based on their matching score using < code > mo_matching_score()< / code > . This matching score \(m\) is calculated as:< / p >
< p > $$m_{(x, n)} = \frac{l_{n} - 0.5 \times \min \begin{cases}l_{n} \\ \operatorname{lev}(x, n)\end{cases}}{l_{n} p k}$$< / p >
< p > where:< / p > < ul >
< li > < p > \(x\) is the user input;< / p > < / li >
< li > < p > \(n\) is a taxonomic name (genus, species and subspecies);< / p > < / li >
< li > < p > \(l_{n}\) is the length of the taxonomic name;< / p > < / li >
< li > < p > \(\operatorname{lev}\) is the < a href = 'https://en.wikipedia.org/wiki/Levenshtein_distance' > Levenshtein distance< / a > function;< / p > < / li >
< li > < p > \(p\) is the human pathogenic prevalence, categorised into group \(1\), \(2\) and \(3\) (see < em > Details< / em > in < code > < a href = 'as.mo.html' > ?as.mo< / a > < / code > ), meaning that \(p = \{1, 2 , 3\}\);< / p > < / li >
< li > < p > \(k\) is the kingdom index, set as follows: Bacteria = \(1\), Fungi = \(2\), Protozoa = \(3\), Archaea = \(4\), and all others = \(5\), meaning that \(k = \{1, 2 , 3, 4, 5\}\).< / p > < / li >
< / ul >
< p > All matches are sorted descending on their matching score and for all user input values, the top match will be returned.< / p >
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< h2 class = "hasAnchor" id = "examples" > < a class = "anchor" href = "#examples" > < / a > Examples< / h2 >
< pre class = "examples" > < span class = 'fu' > < a href = 'as.mo.html' > as.mo< / a > < / span > (< span class = 'st' > "E. coli"< / span > )
< span class = 'fu' > < a href = 'as.mo.html' > mo_uncertainties< / a > < / span > ()
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< span class = 'fu' > mo_matching_score< / span > (< span class = 'st' > "E. coli"< / span > , < span class = 'st' > "Escherichia coli"< / span > )
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