instruction:
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.
question:
In this section, we present results for the 30 countries used for model specification and tuning and compare with the overall results in order to access the extent to which tuning and model specification may have affected results for these countries. We experimented with different model specifications and combinations of features on a subset of data consisting of 30 countries, prior to applying our models to the entire collection of countries. Table 2 -2 presents the model performance metrics for both the entire collection of 72 countries and for the subset of 30 countries used for model specification and tuning. Model performance was slightly diminished on the entire collection of countries compared with the 30 countries used for model specification and tuning. In part, the poorer performance can be explained by the fact that the average number of articles per week in the entire collection of countries was lower than in the 30 countries used for model specification -0.14 articles per week versus 3.50 articles per week. We have shown that in general our models perform best on country-disease pairs that receive substantial news coverage.
answer:
1 - finding, 2 - finding, 3 - finding, 4 - finding, 5 - finding, 6 - finding, 7 - finding

question:
Background: Surveillance of winter respiratory viral illness has been carried out for nearly 30 years using a clinical diagnosis by general practitioners as part of the Scottish Sentinel General Practice (SSGP) network. Contemparaneous laboratory diagnosis has not been available previously. Objectives: To assess the proportion of influenza-like illness (ILI) attributable to influenza, respiratory syncytial virus (RSV) and picornavirus infection during the winter season. To compare the influenza PCR data with serology of paired blood samples. Study design: Combined nose and throat swabs, from patients with ILI attending 15 general practices across Scotland, were submitted to the laboratory in virus PCR sample solution (VPSS). The extracted nucleic acid was tested using a multiplex reverse-transcription polymerase chain reaction (RT-PCR) assay. Serological analysis was performed on paired serum samples using complement fixation assays. The rate of influenza virus positivity was compared with reports of ILI obtained from the SSGP network. Results: Of 240 samples received at the laboratory, 132 (55%) were PCR positive for influenza A virus. There were nine (3.8%) picornavirus and three (1.2%) RSV PCR positives, two (0.8%) were dual influenza A/picornavirus infections. Ninety four (39.2%) were negative for all viruses tested. Results on paired sera from 89 patients showed a rising titre to influenza A in 48 of the 57 PCR positive samples (84.2%). One PCR negative patient displayed a significant rising titre to influenza A. Virological data paralleled the SSGP data but was available at least a week earlier. Conclusions: Influenza A infection was detected in the majority of patients with ILI; picornavirus infection was also shown to be an important cause of illness. PCR is a rapid and sensitive method for respiratory virus surveillance. Serology is slow, insensitive and difficult to interpret at low titres.
answer:
1 - background, 2 - background, 3 - purpose, 4 - purpose, 5 - purpose, 6 - method, 7 - method, 8 - method, 9 - method, 10 - method, 11 - method, 12 - finding, 13 - finding, 14 - finding, 15 - finding, 16 - finding, 17 - finding, 18 - finding, 19 - finding, 20 - finding, 21 - finding

question:
C. Xu et al.
answer:
1 - other