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Carthy started recording for Topic in the mid-70s, an association that continues to this day.
Brainstorm ideas for topic.
From our eight experts, we received 54 questions for topic 1, 47 questions for topic 2, and 40 questions for topic 3.
For topic (3), five papers are included in this issue.
The conceptual motivation for topic modeling is quite straightforward.
This results in a 92.3 % precision rate for topic discovery.
Figure 16 Robustness of profile-based crawler for topic "flower".
Figure 17 Robustness of profile-based crawler for topic "nyc".
Altogether, the students from both institutes posted 301 messages on the three discussion topics (124 for topic 1, 95 for topic 2, and 82 for topic 3) and 263 responses (126 for topic 1, 71 for topic 2, 66 for topic 3).
Figure 10 Crawling harvest ratio for topic "flowers" (threshold = 0. 01). Figure 11 Crawling harvest ratio for topic "nyc" (threshold = 0. 0.).
AHRQ convened a work group to assess approaches and develop recommendations for topic refinement.
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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