In this task, you are given a paragraph (from a research paper) and your task is to classify each sentence of the paragraph (assume n sentence) into the following categories: Background, Purpose, Method, Finding/Contribution, or Other. Return the output in this format: 1 - category of sentence 1, 2 - category of sentence 2, ..., n - category of sentence n; where each number indicates the order of the sentence. The categories can be identified using the following questions: 
 Background: - Why is this problem important? - What relevant works have been done before? - What did the previous works miss? - What are the high-level research questions? - How might this help other researchers?
 Purpose: - What specific things do the researchers want to do? - What specific knowledge do the researchers want to know? - What specific hypothesis do the researchers want to test?
 Method: - How did the researchers do it or find it out? - What are the procedures and steps of this research?
 Finding/Contribution: - What did the researchers find out? Did the proposed methods work? - Did things behave as the researchers expected?
Other: put every text fragment that does not fit into any of the categories above here. Put a sentence here if its not in English, is not part of the article, contains numbers and dates, is a caption of a figure or a table, is a formatting error, or you are not sure about it.

[EX Q]: The video component of this article can be found at jove 15, 23 . The qRT-PCR-based assay described here can detect attachment events using as few as 20 plaque forming units (PFUs) of virus, which translates into an MOI of 0.0004 for a 48-well plate. Therefore, the strong sensitivity of the assay overcomes the requirement for high MOI as well as any virus labeling or concentration steps. Further, the assay can be i) adapted to measure virion endocytosis Journal of Visualized Experiments
[EX A]: 1 - other, 2 - finding, 3 - finding, 4 - finding, 5 - finding

[EX Q]: HealthMap is a useful free and open resource employing text-processing algorithms to identify important disease outbreak information through a user-friendly interface. Ⅲ J Am Med Inform Assoc. 2008;15:150 -157.
[EX A]: 1 - background, 2 - other

[EX Q]: Citation Perlman S, Zhao J. 2013. Human coronavirus EMC is not the same as severe acute respiratory syndrome coronavirus. mBio 4(1):e00002-13.
[EX A]:
1 - other, 2 - finding, 3 - other