Sentence examples for score upper from inspiring English sources

Patient demographics at study enrolment are presented in Table 1, including Fugl-Meyer (FM) score, upper extremities (UE) section [ 45].

The inclusion of study MEM-MD-12 in the combination analysis was justified by PenTAG based on the MMSE score upper range at baseline being 20.37 [ 22].

Symptom severity during the 2 weeks postinfection was derived using daily diary cards to score upper respiratory (cold) and lower respiratory (chest) symptoms as described.

Comparison of an example of a SNP with an average GenCall score (upper panel) to the SNP-locus with the lowest GenCall score (lower panel).

The greatest effects for muscle strength measures (T0 to T4) were found for the MRC sum score upper limbs with a large effect size of 1.28.

The best-possible score (upper bound) of a metric can be obtained by ensuring the maximum quantification of the motif characteristics.

Patients with more frequent dysphagia (question 2: 'Yes') (98.1%) during baseline (visit 2) reported within the highest (worst) range of DSQ scores (upper 25%) exceeding the >60% threshold for acceptability (Table 3).

Figure 16 Stability test of the GMM emotion classifier for male gender; obtained scores (upper set of graphs), and finally determined class of emotion (bottom set); feature set P3, N gmix = 6, N iter = 1200; tested sentence expressed by the male speaker in neutral and emotional styles.

Figure 14 Influence of limited length of feature vector on stability of the GMM emotion classification process; obtained scores (upper set of graphs), determined class of emotion (bottom set); feature sets P3_8, P3_12, and P3_16, N gmix = 6, N iter = 1200; tested sentence expressed by the female speaker in joyous style.

Figure 15 Influence of incorrectly chosen GMM model of gender type on stability of the emotion classification; obtained scores (upper set of graphs), determined class of emotion (bottom set); feature set P3, N gmix = 6, N iter = 1200; tested sentence expressed in neutral speaking style by the male speaker (left two graphs), and by the female speaker (right graphs).

Figure 17 Stability test of the GMM emotion classifier for female gender; obtained scores (upper set of graphs), and finally determined class of emotion (bottom set); feature set P3, N gmix = 6, N iter = 1200; tested sentence expressed by the female speaker in neutral and emotional styles.