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".

Ex Input:
Paragraph: Purpose: COVID-19 has become global threaten. CT acts as an important method of 60 diagnosis. However, human-based interpretation of CT imaging is time consuming. 61 More than that, substantial inter-observer-variation cannot be ignored. We aim at 62 developing a diagnostic tool for artificial intelligence (AI)-based classification of CT 63 images for recognizing COVID-19 and other common infectious diseases of the lung. 64 Experimental Design: In this study, images were retrospectively collected and 65 prospectively analyzed using machine learning. CT scan images of the lung that show 66 or do not show COVID-19 were used to train and validate a classification framework 67 based on convolutional neural network. Five conditions including COVID-19 68 pneumonia, non-COVID-19 viral pneumonia, bacterial pneumonia, pulmonary 69 tuberculosis, and normal lung were evaluated. Training and validation set of images 70 were collected from Wuhan Jin Yin-Tan Hospital whereas test set of images were 71 collected from Zhongshan Hospital Xiamen University and the fifth Hospital of 72 Wuhan. 73 Results: Accuracy, sensitivity, and specificity of the AI framework were reported. For 74 test dataset, accuracies for recognizing normal lung, COVID-19 pneumonia, 75 non-COVID-19 viral pneumonia, bacterial pneumonia, and pulmonary tuberculosis 76 were 99.4%, 98.8%, 98.5%, 98.3%, and 98.6%, respectively. For the test dataset, 77 accuracy, sensitivity, specificity, PPV, and NPV of recognizing COVID-19 were 78 98.8%, 98.2%, 98.9%, 94.5%, and 99.7%, respectively. 79 All rights reserved. No reuse allowed without permission. the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. 
 Title: Deep Learning-Based Recognizing COVID-19 Deep Learning-Based Recognizing COVID-19 and other Common Infectious Diseases of the Lung by Chest CT 2 Scan Images

Ex Output:
False


Ex Input:
Paragraph: Objectives: Cow and calf performance in a semi-confined cow-calf production system was compared with total confinement using summer-born calves. Material and Methods: The experiment was conducted over 3 yr in eastern Nebraska (ENREC) and 2 yr in western Nebraska (PREC) in a randomized complete block design. Lactating, crossbred beef cows (n = 127 at ENREC; n = 56 at PREC) with summer-born calves were used from November to April. Treatments were (1) drylot feeding or (2) cornstalk grazing with supplementation. Dry-lot pairs were limit fed a crop residue and distillersbased diet to meet energy requirements of a lactating cow. A dried distillers grain-based pellet was supplemented to pairs on cornstalks at a rate of 2.4 kg of DM/pair daily. Dry-lot cow-calf pairs were limit fed 12.1 kg of DM/d throughout the trial. Results and Discussion: At ENREC, cows wintered on cornstalks lost BW and had a 0.46-unit decrease in BCS (P < 0.01), whereas cows in the dry-lot gained BW and had a 0.24-unit increase in BCS. At PREC, BCS increased by 0.03 units for cows wintered in the dry-lot and decreased by 0.26 units for cows wintered on cornstalks (P < 0.04). At both locations, calves fed in a dry-lot had greater ADG and BW per day of age compared with calves offered cornstalk grazing with supplementation (P ≤ 0.03). Implications and Applications: A partial budget suggests that lower winter production inputs compensate for reduced performance of calves when cow-calf pairs are wintered on cornstalks, making residue grazing a viable option in partial confinement systems. 
 Title: Performance of cows and summer-born calves and economics in semi-confined and confined beef systems

Ex Output:
False


Ex Input:
Paragraph: Background: Infectious Bronchitis is a highly contagious respiratory disease which causes tracheal lesions and also affects the reproductive tract and is responsible for large economic losses to the poultry industry every year. This is due to both mortality (either directly provoked by IBV itself or due to subsequent bacterial infection) and lost egg production. The virus is difficult to control by vaccination, so new methods to curb the impact of the disease need to be sought. Here, we seek to identify genes conferring resistance to this coronavirus, which could help in selective breeding programs to rear chickens which do not succumb to the effects of this disease. Methods: Whole genome gene expression microarrays were used to analyse the gene expression differences, which occur upon infection of birds with Infectious Bronchitis Virus (IBV). Tracheal tissue was examined from control and infected birds at 2, 3 and 4 days post-infection in birds known to be either susceptible or resistant to the virus. The host innate immune response was evaluated over these 3 days and differences between the susceptible and resistant lines examined. Results: Genes and biological pathways involved in the early host response to IBV infection were determined andgene expression differences between susceptible and resistant birds were identified. Potential candidate genes for resistance to IBV are highlighted. Conclusions: The early host response to IBV is analysed and potential candidate genes for disease resistance are identified. These putative resistance genes can be used as targets for future genetic and functional studies to prove a causative link with resistance to IBV. 
 Title: The early immune response to infection of chickens with Infectious Bronchitis Virus (IBV) in susceptible and resistant birds

Ex Output:

False