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 Input:
Geo-social interaction patterns Geo-social scale Location-based social network Agent-based epidemic models Social network analysis Infectious disease transmission and control High performance computing A B S T R A C T Cities play an important role in fostering and amplifying the transmission of airborne diseases (e.g., influenza) because of dense human contacts. Before an outbreak of airborne diseases within a city, how to determine an appropriate containment area for effective vaccination strategies is unknown. This research treats airborne disease spreads as geo-social interaction patterns, because viruses transmit among different groups of people over geographical locations through human interactions and population movement. Previous research argued that an appropriate scale identified through human geo-social interaction patterns can provide great potential for effective vaccination. However, little work has been done to examine the effectiveness of such vaccination at large scales (e.g., city) that are characterized by spatially heterogeneous population distribution and movement. This article therefore aims to understand the impact of geo-social interaction patterns on effective vaccination in the urbanized area of Portland, Oregon. To achieve this goal, we simulate influenza transmission on a large-scale location-based social network to 1) identify human geo-social interaction patterns for designing effective vaccination strategies, and 2) and evaluate the efficacy of different vaccination strategies according to the identified geo-social patterns. The simulation results illustrate the effectiveness of vaccination strategies based on geosocial interaction patterns in containing the epidemic outbreak at the source. This research can provide evidence to inform public health approaches to determine effective scales in the design of disease control strategies.

Ex Output:
1 - background, 2 - background, 3 - background, 4 - background, 5 - background, 6 - background, 7 - background, 8 - purpose, 9 - method, 10 - method, 11 - finding, 12 - finding

Ex Input:
One sentence summary: A systematic review and meta-analysis of randomised clinical trials investigating antimicrobial prophylaxis or metaphylaxis against naturally occurring bovine respiratory disease. Editor: Edmundo Calva ABSTRACT A distinct difference between veterinary and human medicine is the routine use of antimicrobial mass medications (prophylaxis, metaphylaxis) to healthy individuals. The need for antimicrobial mass medications is based on beliefs that group/s of animals will contract a bacterial disease (i.e. morbidity) and/or die (i.e. mortality). Bovine respiratory disease (BRD) represents the major indication for cattle antimicrobials worldwide. The objectives were to perform a systematic review and meta-analysis of randomised controlled clinical trials (RCTs) for naturally occurring BRD investigating antimicrobial prophylaxis/metaphylaxis to prevent morbidity/mortality. In total, 58 publications met the inclusion criteria summarizing 169 individual RCTs, spanning 50 years . Antimicrobial prophylaxis and metaphylaxis demonstrated moderate, yet highly variable relative risk reductions in BRD morbidity. These were dependent on the antimicrobial classes used, dependent on metaphylaxis definition, BRD attack rates and duration of the RCTs. Best relative risk reductions were from broad-spectrum critically important antimicrobials, or combinations. BRD prophylaxis/metaphylaxis represents major antimicrobial consumption for highly variable short-term gains in absolute risk reduction of morbidity/mortality. Despite widespread use of prevention products, the need for antimicrobial mass medications should be re-evaluated since the underlying problem is more likely the segmented infrastructure of the feedlot and veal calf industries compared to the disease itself.

Ex Output:
1 - background, 2 - background, 3 - background, 4 - background, 5 - purpose, 6 - method, 7 - finding, 8 - finding, 9 - finding, 10 - finding, 11 - finding, 12 - finding, 13 - finding, 14 - finding

Ex Input:
The limit of blanks (LoBs) of the RT-dPCR assays were ~1.6, ~1.6 and ~0.8 copies/reaction for ORF 1ab, N and E genes, respectively. The limit of detection (LoD) was 2 copies/reaction. For the 103 fever suspected patients, the sensitivity of SARS-CoV-2 detection was significantly improved from 28.2% by RT-qPCR to 87.4% by RT-dPCR. For close contacts, the suspect rate was greatly decreased from 21% down to 1%. The overall sensitivity, specificity and diagnostic accuracy of RT-dPCR were 90%, 100% and 93 %, respectively. In addition, quantification of the viral load for convalescents by RT-dPCR showed that a longer observation period was needed in the hospital for elderly patients.

Ex Output:
1 - finding, 2 - finding, 3 - finding, 4 - finding, 5 - finding, 6 - finding, 7 - finding, 8 - finding, 9 - finding, 10 - finding