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We are particularly interested in the correct classification of the positive and negative tweets.
We observe that, at the expense of a very slight reduction in the correct classification rate for color-mix images, our new classification strategy results in significant improvements of the correct classification rates of photo and mono-text documents.
However, the amount of the increase in the correct classification rate is relatively small.
The amount of the decrease in the correct classification was also relatively small.
Thus, relative to 3q26, these five specimens exhibited loss of 3p and 3q11, resulting in the correct classification of the specimens as ccRCC.
Since Protein G and anti-deer conjugates resulted in the correct classification of a similar number of animals, and since Protein G is more readily available to end-users, we selected this conjugate to proceed with further testing.
Similar(50)
In addition, the correct classification of patients allowed to reconsider their need for hospitalization in MDR-TB wards limiting nosocomial exposure to MDR-TB.
In addition, the correct classification of real pre-miRNAs (positive samples) has greater value than the correct classification of pseudo pre-miRNAs (negative samples).
Our results are comparable to the previous results in terms of the correct classification of acute admissions in 97% and 98.6% of cases.
In sentinel lymph node positive samples, 22/27 samples were correctly classified, in comparison to the correct classification of 55/71 sentinel lymph node negative samples.
We also include in Table 1 the correct classification ratio.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com