Sentence examples for score distance from inspiring English sources

Exact(17)

You can also choose how restaurants are sorted – best match, Google rating, Zagat food score, distance, or pricing.

The constructed score database4 includes the matching score distance matrices and the subject ID list along with the quality measures (i.e., the SRs, TRs, and views).

As a result, we can draw on N TR score distance matrices with 1912 N TR genuine (true match) scores and 1912 N TR × 1,911 = 3,653,832 N TR imposter (false match) scores for each biometric modality and quality, which results in a very large-scale database containing 3,908,128 genuine scores and 7,468,432,608 imposter scores for each modality.

The matrix score, conservation score, distance from gene start and coding/non-coding values were assigned to every TFBS match.

A Perl script (Phylip_tree_distance.pl) was used to run the PHYLIP treedist program to determine the distance between the RA and MLST trees using the Branch Score Distance [33].

Branch Score Distance (BSD) between the optimal AAF tree and trees generated with larger k.

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Similar(43)

GPS does not use standard machine learning approaches but implements a so-called group-based scoring technique, which makes use of the BLOSUM62 matrix to score distances between query sequences and known clusters of kinase substrate peptides [ 15, 16].

The evaluation of the performance of the dimensionality reduction techniques and introduced descriptor spaces to separate different activity classes has been monitored by three parameters (Г-score, Distance Consistency and Distribution Consistency) and their efficiency was compared.

This technique is called "Principal Component Scores Distance Analysis" (PC-SDA).

We compared each pair of trees using normalized versions of standard measures of topological error (normalized Robinson-Foulds distance (nRF)) and branch-length error (normalized branch-score distance (nBS)) [ 19] (see Additional file 8: Supplementary Methods).

We defined significant network motifs as motifs that occurred significantly more often in the inferred networks than in the randomized networks, and ranked these motifs by their Z-score distance to the randomized tests.

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