Sample: 1
ID: X00016469670
Recall: 100.00%
Precision: 100.00%
Hmean: 100.00%
Sample: 2
ID: X00016469671
Sample: 3
ID: X51005200931
Recall: 98.77%
Hmean: 99.38%
Sample: 4
ID: X51005230605
Sample: 5
ID: X51005230616
Sample: 6
ID: X51005230621
Recall: 98.15%
Hmean: 99.07%
Sample: 7
ID: X51005230648
Sample: 8
ID: X51005230657
Recall: 97.89%
Precision: 99.30%
Hmean: 98.59%
Sample: 9
ID: X51005230659
Recall: 96.67%
Precision: 96.11%
Hmean: 96.39%
Sample: 10
ID: X51005268275
Recall: 98.43%
Precision: 98.02%
Hmean: 98.22%
Sample: 11
ID: X51005268408
Sample: 12
ID: X51005288570
Sample: 13
ID: X51005301666
Recall: 97.30%
Precision: 98.68%
Hmean: 97.99%
Sample: 14
ID: X51005337867
Sample: 15
ID: X51005337877
Recall: 98.11%
Hmean: 99.05%
Sample: 16
ID: X51005361906
Precision: 97.56%
Hmean: 98.16%
Sample: 17
ID: X51005361908
Recall: 96.39%
Precision: 94.60%
Hmean: 95.49%
Sample: 18
ID: X51005361912
Recall: 96.77%
Precision: 96.77%
Hmean: 96.77%
Sample: 19
ID: X51005361923
Precision: 97.06%
Hmean: 98.51%
Sample: 20
ID: X51005365187
Recall: 97.17%
Hmean: 98.56%