TASK DEFINITION: In this task, you're given a paragraph and title from the research paper. Your task is to classify whether the given title is suitable or not for the research paper based on the given paragraph. Return "True" if title is proper according to paragraph else "False".
PROBLEM: Paragraph: The recent coronavirus pandemic follows in its early stages an almost exponential expansion, with the number of cases as a function of time reasonably well fit by N (t) ∝ e αt , in many countries. We analyze the rate α in different countries, choosing as a starting point in each country the first day with 30 cases and fitting for the following 12 days, capturing thus the early exponential growth in a rather homogeneous way. We look for a link between the rate α and the average temperature T of each country, in the month of the epidemic growth. We analyze a base set of 42 countries, which developed the epidemic earlier, and an extended set of 88 countries, which developed the epidemic more recently. Fitting with a linear behavior α(T ), we find evidence in both datasets for a decreasing growth rate as a function of T , at 99.66%C.L. and 99.86%C.L. in the base and extended dataset, respectively. In the base set, going beyond a linear model, a peak at about (7.7 ± 3.6) • C seems to be present in the data. Our findings give hope that, for northern hemisphere countries, the growth rate should significantly decrease as a result of both warmer weather and lockdown policies. In general the propagation should be hopefully stopped by strong lockdown, testing and tracking policies, before the arrival of the next cold season. I. 
 Title: Temperature dependence of COVID-19 transmission

SOLUTION: True

PROBLEM: Paragraph: LETTERS that the quantitative assessment of the effectiveness of public health intervention measures for SARS is a difficult task for modelers. To make models useful for assessing the effects of specific intervention measures and for predicting the future dynamics during an ongoing epidemic, we need improved knowledge on the transmission mechanisms, pathogenesis, and the epidemiologic determinants of the spread of the virus. Any retrospective analysis of the 2003 SARS epidemic that improves our knowledge of SARS epidemiology is welcome. 
 Title: SARS epi-demiology and cumulative case curve

SOLUTION: False

PROBLEM: Paragraph: The COMBINE method was designed to study congeneric series of compounds including structural information of ligandprotein complexes. Although very successful, the method has not received the same level of attention than other alternatives to study Quantitative Structure Active Relationships (QSAR) mainly because lack of ways to measure the uncertainty of the predictions and the need for large datasets. Active learning, a semi-supervised learning approach that makes use of uncertainty to enhance models' performance while reducing the size of the training sets, has been used in this work to address both problems. We propose two estimators of uncertainty: the pool of regressors and the distance to the training set. The performance of the methods has been evaluated by testing the resulting active learning workflows in 3 diverse datasets: HIV-1 protease inhibitors, Taxol-derivatives and BRD4 inhibitors. The proposed strategies were successful in 80% of the cases for the taxol-derivatives and BRD4 inhibitors, while outperformed random selection in the case of the HIV-1 protease inhibitors time-split. Our results suggest that AL-COMBINE might be an effective way of producing consistently superior QSAR models with a limited number of samples. 
 Title: Active learning strategies with COMBINE analysis: new tricks for an old dog

SOLUTION:
True