<|begin_of_text|><|start_header_id|>system<|end_header_id|>You are an expert on climate change, human mobility and migration. Answer the question truthfully.<|eot_id|><|start_header_id|>user<|end_header_id|>Here are the title and abstract of a scientific paper probably related to climate change, human mobility and migration..
Title:"Gauging human mobility characteristics and its impact on mobile routing performance."
Abstract:"A new generation of 'behaviour-aware' services are emerging, defining the future mobile social networks. It is important for current mobility models to capture mobile users' behavioural characteristics and also reproduce their effects on the performance of networking protocols. Recent work in mobility modelling focused on replicating metrics of encounter statistics and spatio-temporal preferences. In this study, we attempt to show the sufficiency (or inadequacy) of these mobility metrics in reproducing realistic performance of networking protocols. We provide three main findings: (a) careful parameterisation of the models can replicate mobility metrics; (b) a rich set of communities in real mobile societies exist with distinct behavioural clusters of users; (c) even carefully crafted models surprisingly result in structural dynamics and protocol performance that is dramatically different from the trace-driven performance. These findings strongly suggest a need to re-visit mobility modelling to incorporate accurate behavioural characteristics.."
I have six questions you need to answer.
Q1: Is this article is about 'human migration mobility': 1 = yes; 0 = no. Answer with a number. Do not give a textual explanation.

Q2: What drivers of migration and mobility does the article study? 0 = 'other', 1 = 'climate', 2 = 'environment', 3 = 'economic', 4 = 'conflict', 5 = 'political', 6 = 'social', 7 = 'family'. Answer with a number or a sequence of numbers separated by commas. Do not give a textual explanation. 

Q3: What is the overall sentiment of the article?:0 = 'neutral', 1 = 'negative', 2 = 'positive'. Answer with a number. Do not give a textual explanation.

Q4: What type of climate or environmental keywords are explicitly mentioned?:  0 = 'none', 1 = 'algal blooms', 2 = 'infestation', 3 = 'infectious diseases', 4 = 'ocean acidification', 5 = 'sea ice', 6 = 'acid rain', 7 = 'drought', 8 = 'cold wave', 9 = 'heat wave', 10 = 'glacial', 11 = 'wildfire', 12 = 'air pollution', 13 = 'biodiversity loss', 14 = 'coastal erosion', 15 = 'land degradation', 16 = 'deforestation', 17 = 'desertification', 18 = 'water pollution', 19 = 'diebacks', 20 = 'permafrost loss', 21 = 'sand mining', 22 = 'sea level rise', 23 = 'earthquake', 24 = 'tsunami', 25 = 'volcanic', 26 = 'flood', 27 = 'avalanche', 28 = 'landslide', 29 = 'downburst', 30 = 'thunderstorm', 31 = 'sandstorm', 32 = 'haze', 33 = 'storm', 34 = 'cyclone', 35 = 'blizzard', 36 = 'hail', 37 = 'snow', 38 = 'tornado', 39 = 'wind', 40 = 'hurricane', 41 = 'typhoon', 42 = 'other'. Answer with a number or a sequence of numbers separated by commas. Do not give a textual explanation. 

Q5: What discipline does the article belong to?: 0 = 'other', 1 = 'social science', 2 = 'natural science', 3 = 'arts and humanities', 4 = 'multidiscipline and interdiscipline'. Answer with a number. Do not give a textual explanation.

Q6: Does the article apply quantitative and/or statistical analysis?: 0 = 'no', 1 = 'yes'. Answer with a number. Do not give a textual explanation.

Use the following template: 

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Q6 = [].<|eot_id|><|start_header_id|>assistant<|end_header_id|>Answer:

Gauging human mobility characteristics and its impact on mobile routing performance
A new generation of 'behaviour-aware' services are emerging, defining the future mobile social networks. It is important for current mobility models to capture mobile users' behavioural characteristics and also reproduce their effects on the performance of networking protocols. Recent work in mobility modelling focused on replicating metrics of encounter statistics and spatio-temporal preferences. In this study, we attempt to show the sufficiency (or inadequacy) of these mobility metrics in reproducing realistic performance of networking protocols. We provide three main findings: (a) careful parameterisation of the models can replicate mobility metrics; (b) a rich set of communities in real mobile societies exist with distinct behavioural clusters of users; (c) even carefully crafted models surprisingly result in structural dynamics and protocol performance that is dramatically different from the trace-driven performance. These findings strongly suggest a need to re-visit mobility modelling to incorporate accurate behavioural characteristics.