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Table 3 Accident frequency distribution and categorization Cluster id Number of locations Accident frequency Total accidents % Accidents Category name 1 56 30–75 2,646 36.11 LFAL 2 22 75–150 2,569 35.06 MFAL 3 8 150–303 2,112 28.82 HFAL.
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Examples of text mining applications are "information extraction, topic tracking, summarization, categorization, clustering, concept linkage, information visualization, or question answering" [75].
Functional classification – Clusters were assigned putative functional categorization using two methods.
Repeating the analysis with different categorizations of cluster size gave similar results (not shown).
A more analytical categorization of clustering algorithms can be found at [ 110, 116].
Categorization of clusters in Danish, migrant or uncertain origin is a simplification with many limitations.
There was complete agreement (100%) between map book cluster categorization and GPS cluster categorization, with a κ statistic of 1.00 (bias-corrected 95% CI: 1.00, 1.00).
Interrater agreement between the 2 research assistants for Method 1 and agreement between cluster categorization with the map book system and GPS cluster categorization were assessed by using the κ statistic.
The configuration of the final map for each of the sub-groups resulted essentially from the cluster categorization exercise.
A research assistant blinded to map book cluster categorization then took a set of GPS coordinates from each ART initiator's household during a home visit.
Functional categorization by COG (Cluster of Orthologous Groups [ 32]) classification of the predicted proteome of the sequenced strains (Additional files 2 and 3) revealed a largely identical functional repertoire in the seven sequenced strains with the largest variance between strains in the percentage of proteins assigned to COG functional category L (replication, recombination and repair).
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