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.

Results: High prices of medicinal plants are widely considered to reflect resource scarcity. Real-time market prices for three of the four very different TCM species we studied all showed major price fluctuations. The exception was P. polyphylla, whose wild populations are widely known to be increasingly scarce, where there was a steady increase in price, with few fluctuations in the upward price trend. The three other species showed significant price fluctuations. These were driven by multiple factors. Ecological and biogeographic factors that influence abundance or scarcity of supply certainly played a role. But other factors were also influential. These included both national and global economic factors (the influence of the Global Financial Crisis (GFC)), national policy changes that in turn influenced businessmen giving expensive gifts (that included O. sinensis)), climate change (influencing fruiting success of S. sphenanthera), price speculation by traders and lack of information (e.g: reduction in G. gecko prices due to traders incorrectly believing that domestication would increase supplies). Conclusions: Price fluctuations in the four TCM species we examined are influenced by many factors and not just resource scarcity. And the situation is more complex than the trajectory based on Homma's (1992) model, where he predicted that higher prices would result in a shift to cultivation, thus replacing wild harvest. In case of both O. sinensis and P. polyphylla, Homma (1992 Homma ( , 1996 was right in terms of scarcity and high prices stimulating a major investment in cultivation (P. polyphylla) and artificial production (O. sinensis). But in both cases, intensive production through cultivation or artificial propagation do not yet occur on a large enough scale to reduce harvest of wild stocks. Substitution and adulteration occur with all four species. Improving information to doi.
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The objectives of this study were to evaluate the effects of free-access acidified milk replacer feeding on the pre-and postweaning health of dairy and veal calves. Individually housed calves were systematically assigned at birth to 1 of 2 feeding programs: free-access feeding (ad libitum) of acidified milk replacer (ACD, n = 249) or traditional restricted feeding (3 L fed twice daily) of milk replacer (RES, n = 249). Calves were fed milk replacer containing 24% crude protein and 18% fat. Acidified milk replacer was prepared to a target pH between 4.0 and 4.5 using formic acid. Calves were weaned off milk replacer at approximately 6 wk of age. Weaning occurred over 5 d, and during this weaning period, ACD calves had access to milk replacer for 12 h/d and RES calves were offered only one feeding of milk replacer (3 L) daily. Calves were monitored daily for signs of disease. Fecal consistency scores were assigned each week from birth until weaning. A subset of calves was systematically selected for fecal sampling at 3 time points between 7 and 27 d of age. Fecal samples were analyzed for enterotoxigenic Escherichia coli F5, Cryptosporidium parvum, rotavirus, and coronavirus. Hip width, hip height, body length, heart girth, and body weight were measured at birth and weaning. Postweaning body weight measurements were collected from the heifers at approximately 8 mo of age. Postweaning body weight and carcass grading information was collected from the veal calves at slaughter once a live weight between 300 and 350 kg had been achieved. The odds of ACD calves being treated for a preweaning disease event tended to be lower than that of the RES calves (1.2 vs. 5.2%, respectively). Preweaning mortality, postweaning disease treatment, and postweaning mortality did not differ between feeding treatments. The ACD feeding treatment supported greater preweaning average daily gain (0.59 vs. 0.43 kg/d) and structural growth than RES feeding. Postweaning average daily gain and carcass characteristics were similar for ACD and RES calves. These results indicate that free-access acidified milk replacer feeding tended to support improved health, and greater body weight gain and structural growth during the preweaning period; these effects did not persist in the postweaning period. The growth advantage observed before weaning in the ACD calves likely disappeared due to the weaning methods used.
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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.

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